Showing posts with label Artificial Intelligence. Show all posts
Showing posts with label Artificial Intelligence. Show all posts
Intro to AI Agents and Agentic AI
Friday, May 15, 2026
Intro to AI Agents and Agentic AI
Understand How AI Agents Work and How to Leverage This Technology to Transform Your Business and Career
Preview this Course
Artificial Intelligence is evolving at a breathtaking pace. Just when we thought Large Language Models (LLMs) like ChatGPT were the peak, a new paradigm is emerging: Agentic AI. But what exactly are AI Agents, and why are they considered the next frontier in technology?
If you are looking to understand this shift from passive chatbots to autonomous problem-solvers, the comprehensive course "Intro to AI Agents and Agentic AI" on Udemy is the perfect starting point. Here is a summary of why this topic is trending and what you can expect to learn.
From Chatbots to Agents: The Shift in Autonomy
Traditional AI models operate on a "request-response" basis. You ask a question; it answers. However, AI Agents change the game. An AI Agent doesn't just generate text; it takes action. It can:
Reason: Break down complex goals into smaller steps.
Use Tools: Browse the web, run code, or access databases to gather information.
Autonomy: Make decisions and execute tasks with minimal human intervention.
This shift is moving us from "Generative AI" to "Agentic AI"—systems that can plan, execute, and self-correct to achieve specific objectives.
What You Will Learn in the Course
The course "Intro to AI Agents and Agentic AI" is designed to demystify these concepts, whether you are a developer, a tech enthusiast, or a business leader. The curriculum provides a structured introduction to the architecture and ecosystem of AI agents.
Key highlights include:
Understanding the Core Concepts: A clear breakdown of what defines an AI Agent and how it differs from standard LLMs.
Agent Architectures: Learning the building blocks, including LLMs, memory, planning tools, and retrieval systems (RAG).
The Ecosystem: An overview of popular frameworks and tools that are currently powering the development of agents.
Real-World Applications: How agents are being used today to automate workflows, coding, and data analysis.
Why You Should Enroll Now
As AI technology matures, the demand for professionals who understand how to build and manage autonomous agents is skyrocketing. Understanding "Agentic AI" is no longer optional for those wanting to stay ahead in the tech industry; it is becoming essential.
This course offers a beginner-friendly yet deep dive into the mechanics of these intelligent systems, ensuring you are not left behind in the AI revolution.
Ready to Start Your Journey?
You can gain access to this insightful course today. To help you get started, here is an exclusive offer to enroll at a discount.
👉 Click here to enroll in "Intro to AI Agents and Agentic AI"
Use Coupon Code: UDEAFFHP22025
Don't just watch the AI revolution happen—be a part of building it. Enroll now and master the future of AI!
The AI Engineer Course 2026: Complete AI Engineer Bootcamp
Tuesday, April 28, 2026
Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs
Preview this Course
Description
The Problem
AI Engineers are best suited to thrive in the age of AI. It helps businesses utilize Generative AI by building AI-driven applications on top of their existing websites, apps, and databases. Therefore, it’s no surprise that the demand for AI Engineers has been surging in the job marketplace.
Supply, however, has been minimal, and acquiring the skills necessary to be hired as an AI Engineer can be challenging.
So, how is this achievable?
Universities have been slow to create specialized programs focused on practical AI Engineering skills. The few attempts that exist tend to be costly and time-consuming.
Most online courses offer ChatGPT hacks and isolated technical skills, yet integrating these skills remains challenging.
The Solution
AI Engineering is a multidisciplinary field covering:
AI principles and practical applications
Python programming
Natural Language Processing in Python
Large Language Models and Transformers
Developing apps with orchestration tools like LangChain
Vector databases using PineCone
Creating AI-driven applications
Each topic builds on the previous one, and skipping steps can lead to confusion. For instance, applying large language models requires familiarity with Langchain—just as studying natural language processing can be overwhelming without basic Python coding skills.
So, we created the AI Engineer Bootcamp 2024 to provide the most effective, time-efficient, and structured AI engineering training available online.
This pioneering training program overcomes the most significant barrier to entering the AI Engineering field by consolidating all essential resources in one place.
Our course is designed to teach interconnected topics seamlessly—providing all you need to become an AI Engineer at a significantly lower cost and time investment than traditional programs.
The Skills
1. Intro to Artificial Intelligence
Structured and unstructured data, supervised and unsupervised machine learning, Generative AI, and foundational models—these familiar AI buzzwords; what exactly do they mean?
Why study AI? Gain deep insights into the field through a guided exploration that covers AI fundamentals, the significance of quality data, essential techniques, Generative AI, and the development of advanced models like GPT, Llama, Gemini, and Claude.
2. Python Programming
Mastering Python programming is essential to becoming a skilled AI developer—no-code tools are insufficient.
Python is a modern, general-purpose programming language suited for creating web applications, computer games, and data science tasks. Its extensive library ecosystem makes it ideal for developing AI models.
Why study Python programming?
Python programming will become your essential tool for communicating with AI models and integrating their capabilities into your products.
3. Intro to NLP in Python
Explore Natural Language Processing (NLP) and learn techniques that empower computers to comprehend, generate, and categorize human language.
Why study NLP?
NLP forms the basis of cutting-edge Generative AI models. This program equips you with essential skills to develop AI systems that meaningfully interact with human language.
4. Introduction to Large Language Models
This program section enhances your natural language processing skills by teaching you to utilize the powerful capabilities of Large Language Models (LLMs). Learn critical tools like Transformers Architecture, GPT, Langchain, HuggingFace, BERT, and XLNet.
Why study LLMs?
This module is your gateway to understanding how large language models work and how they can be applied to solve complex language-related tasks that require deep contextual understanding.
5. Building Applications with LangChain
LangChain is a framework that allows for seamless development of AI-driven applications by chaining interoperable components.
Why study LangChain?
Learn how to create applications that can reason. LangChain facilitates the creation of systems where individual pieces—such as language models, databases, and reasoning algorithms—can be interconnected to enhance overall functionality.
6. Vector Databases
With emerging AI technologies, the importance of vectorization and vector databases is set to increase significantly. In this Vector Databases with Pinecone module, you’ll have the opportunity to explore the Pinecone database—a leading vector database solution.
Why study vector databases?
Learning about vector databases is crucial because it equips you to efficiently manage and query large volumes of high-dimensional data—typical in machine learning and AI applications. These technical skills allow you to deploy performance-optimized AI-driven applications.
7. Speech Recognition with Python
Dive into the fascinating field of Speech Recognition and discover how AI systems transform spoken language into actionable insights. This module covers foundational concepts such as audio processing, acoustic modeling, and advanced techniques for building speech-to-text applications using Python.
Why study speech recognition?
Speech Recognition is at the core of voice assistants, automated transcription tools, and voice-driven interfaces. Mastering this skill enables you to create applications that interact with users naturally and unlock the full potential of audio data in AI solutions.
What You Get
$1,250 AI Engineering training program
Active Q&A support
Essential skills for AI engineering employment
AI learner community access
Completion certificate
Future updates
Real-world business case solutions for job readiness
We're excited to help you become an AI Engineer from scratch—offering an unconditional 30-day full money-back guarantee.
With excellent course content and no risk involved, we're confident you'll love it.
Why delay? Each day is a lost opportunity. Click the ‘Buy Now’ button and join our AI Engineer program today.
Who this course is for:
- You should take this course if you want to become an AI Engineer or if you want to learn about the field
- This course is for you if you want a great career
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
Certified AI Engineering Masterclass: From Zero to AI Hero
Sunday, November 23, 2025
Master AI Engineering: Build, Train, and Deploy Scalable AI Solutions with Real-World Projects and Hands-On Learning.(AI
Preview this Course
Description
Welcome to the AI Engineering Masterclass: From Zero to AI Hero! This comprehensive AI course is designed to take you on an exciting journey from an AI beginner to a confident AI Engineer, equipped with the skills to build, train, and deploy Artificial Intelligence solutions. Whether you're starting from scratch or looking to solidify your AI expertise, this AI Masterclass provides the step-by-step roadmap you need to succeed.
In this AI Engineering Masterclass, you'll begin with the foundations of AI, exploring Python programming, data preprocessing, and the basics of machine learning. As you progress, you'll dive into advanced AI topics such as neural networks, deep learning, natural language processing (NLP), and computer vision. You’ll also gain hands-on experience with cutting-edge AI frameworks like TensorFlow, PyTorch, and Hugging Face to create production-ready AI solutions.
This AI Masterclass emphasizes practical AI skills, with real-world projects embedded into every module. You'll learn to tackle real business problems using AI technologies, optimize AI models, and deploy scalable solutions.
Why Choose the AI Engineering Masterclass?
Beginner-Friendly AI Curriculum: Start from scratch and grow into an expert
Hands-On AI Projects: Build real AI applications for real-world challenges
Master AI Frameworks: Learn TensorFlow, PyTorch, and Hugging Face
Comprehensive AI Training: Cover Python, Machine Learning, Deep Learning, NLP, and AI Deployment
Zero to AI Hero Roadmap: Structured learning path for complete AI mastery
By the end of this AI Engineering Masterclass, you'll not only have mastered AI engineering skills, but you'll also be equipped to innovate, lead AI projects, and drive transformation with AI solutions in your organization or startup.
Whether you're an aspiring AI Engineer, an AI enthusiast, or someone looking to break into the Artificial Intelligence industry, this AI Masterclass is your ultimate resource to go From Zero to AI Hero.
Join the AI Revolution Today – Enroll in the AI Engineering Masterclass: From Zero to AI Hero and take the first step towards mastering AI!
Who this course is for:
- Aspiring AI Engineers: Individuals looking to kickstart a career in AI with hands-on skills and real-world projects.
- Data Scientists & Analysts: Professionals aiming to expand their expertise with AI model building and deployment.
- Software Developers: Programmers eager to integrate AI capabilities into their applications and systems.
- Career Changers: Individuals from non-technical backgrounds ready to transition into the AI industry.
- Graduate Students: Students in data science, computer science, or related fields seeking practical AI knowledge.
- Tech Entrepreneurs: Founders and CTOs exploring AI for product innovation and business growth.
- AI Enthusiasts: Anyone passionate about AI and looking to build intelligent systems from scratch.
- Business Professionals: Leaders aiming to understand AI for strategic decision-making and organizational growth.
Artificial Intelligence for Business + ChatGPT Prize [2025]
Sunday, October 26, 2025
Free Coupon Discount - Artificial Intelligence for Business + ChatGPT Prize [2025], Solve Real World Business Problems with AI Solutions
Created by Hadelin de Ponteves Kirill Eremenko SuperDataScience Team
Students also bought
- Unsupervised Deep Learning in Python
- Cluster Analysis and Unsupervised Machine Learning in Python
- Advanced AI: Deep Reinforcement Learning in Python
- Cutting-Edge AI: Deep Reinforcement Learning in Python
- Deep Learning: Recurrent Neural Networks in Python
- Deep Learning Prerequisites: Linear Regression in Python
Preview this Udemy Course GET COUPON CODE
Description
Structure of the course:
Part 1 - Optimizing Business Processes
Case Study: Optimizing the Flows in an E-Commerce Warehouse
AI Solution: Q-Learning
Part 2 - Minimizing Costs
Case Study: Minimizing the Costs in Energy Consumption of a Data Center
AI Solution: Deep Q-Learning
Part 3 - Maximizing Revenues
Case Study: Maximizing Revenue of an Online Retail Business
AI Solution: Thompson Sampling
Real World Business Applications:
With Artificial Intelligence, you can do three main things for any business:
Optimize Business Processes
Minimize Costs
Maximize Revenues
We will show you exactly how to succeed these applications, through Real World Business case studies. And for each of these applications we will build a separate AI to solve the challenge.
In Part 1 - Optimizing Processes, we will build an AI that will optimize the flows in an E-Commerce warehouse.
In Part 2 - Minimizing Costs, we will build a more advanced AI that will minimize the costs in energy consumption of a data center by more than 50%! Just as Google did last year thanks to DeepMind.
In Part 3 - Maximizing Revenues, we will build a different AI that will maximize revenue of an Online Retail Business, making it earn more than 1 Billion dollars in revenue!
But that's not all, this time, and for the first time, we’ve prepared a huge innovation for you. With this course, you will get an incredible extra product, highly valuable for your career:
"a 100-pages book covering everything about Artificial Intelligence for Business!".
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Artificial Intelligence with Machine Learning, Deep Learning
Friday, June 13, 2025
Description
Hello there,
Welcome to the “Artificial Intelligence with Machine Learning, Deep Learning ” course.
Artificial intelligence, Machine learning python, python, machine learning, Django, ethical hacking, python Bootcamp, data analysis, machine learning python, python for beginners, data science, machine learning, Django
Artificial Intelligence (AI) with Python Machine Learning and Python Deep Learning, Transfer Learning, Tensorflow
It’s hard to imagine our lives without machine learning. Predictive texting, email filtering, and virtual personal assistants like Amazon’s Alexa and the iPhone’s Siri, are all technologies that function based on machine learning algorithms and mathematical models.
Ai, TensorFlow, PyTorch, scikit learn, reinforcement learning, supervised learning, teachable machine, python machine learning, TensorFlow python, ai technology, azure machine learning, semi-supervised learning, deep neural network, artificial general intelligence
Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, my course on Udemy is here to help you apply machine learning to your work.
Data Science Careers Are Shaping The Future
Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So data science careers are in high demand.
Udemy offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies. Whether you’re interested in machine learning, data mining, or data analysis, Udemy has a course for you.
If you want to learn one of the employer’s most requested skills?
If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?
If you are an experienced developer and looking for a landing in Data Science!
In all cases, you are at the right place!
We've designed for you “Artificial Intelligence with Machine Learning, Deep Learning” a straightforward course for Python Programming Language and Machine Learning.
In the course, you will have down-to-earth way explanations with projects. With this course, you will learn machine learning step-by-step. I made it simple and easy with exercises, challenges, and lots of real-life examples.
We will open the door of the Data Science and Machine Learning a-z world and will move deeper. You will learn the fundamentals of Machine Learning A-Z and its beautiful libraries such as Scikit Learn.
Throughout the course, we will teach you how to artificial intelligence and fundamentals of machine learning and use powerful machine learning python algorithms.
Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.
Interested in the field of Machine Learning? Then this course is for you! It was designed by two professional Data Scientists who will share their knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way. They will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
Learn python and how to use it to python data analysis and visualization, present data. Includes tons of code data visualization.
In this course, you will learn artificial intelligence, machine learning, deep learning.
Also during the course, you will learn:
This Machine Learning course is for everyone!
My "Machine Learning with Hands-On Examples in Data Science" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).
Why do we use a Python programming language in Machine learning?
Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.
What you will learn?
In this course, we will start from the very beginning and go all the way to the end of "Artificial intelligence with Machine Learning" with examples.
Before each lesson, there will be a theory part. After learning the theory parts, we will reinforce the subject with practical examples.
During the course you will learn the following topics:
What is Machine Learning?
What is AI (artificial intelligence)?
More About Machine Learning
Machine Learning Terminology
Evaluation Metrics
What is Classification vs Regression?
Evaluating Performance-Classification Error Metrics
Evaluating Performance-Regression Error Metrics
Machine Learning with Python
Supervised Learning
artificial intelligence
Machine learning
Machine learning python
Ethical hacking, python Bootcamp
Fundamentals of Data analysis
Python machine learning
Python programming
Python examples
Python hands-on
Deep learning a-z
Machine learning a-z
Machine learning & data science a-z
machine learning algorithms
unsupervised learning
transfer learning
what is numpy?
what is data science?
With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.
Artificial intelligence is growing exponentially. There is no doubt about that. But the further AI advances, the more complex the problems it needs to solve become. The only way to solve such complex problems is with Deep Learning — which is why it's at the heart of Artificial Intelligence. This course will help understand the broad and complex concept of Deep Learning in a robust, organized structure. You will be working on real-world data sets to help you be confident in all the techniques on an instinctual level.
This course has suitable for everybody who is interested in Machine Learning and Deep Learning concepts.
First of all, in this course, we will learn some fundamental stuff of Python and the Numpy library. These are our first steps in our Deep Learning journey. After then we take a little trip to Machine Learning history. Then we will arrive at our next stop. Machine Learning. Here we learn the machine learning concepts, machine learning workflow, models and algorithms, and what is neural network concept. After then we arrive at our next stop. Artificial Neural network. And now our journey becomes an adventure. In this adventure we'll enter the Keras world then we exit the Tensorflow world. Then we'll try to understand the Convolutional Neural Network concept. But our journey won't be over. Then we will arrive at Recurrent Neural Network and LTSM. We'll take a look at them. After a while, we'll trip to the Transfer Learning concept. And then we arrive at our final destination. Projects. Our play garden. Here we'll make some interesting machine learning models with the information we've learned along our journey.
During the course you will learn:
What is the AI, Machine Learning, and Deep Learning
History of Machine Learning
Turing Machine and Turing Test
The Logic of Machine Learning such as
Understanding the machine learning models
Machine Learning models and algorithms
Gathering data
Data pre-processing
Choosing the right algorithm and model
Training and testing the model
Evaluation
Artificial Neural Network with these topics
What is ANN
Anatomy of NN
The Engine of NN
Tensorflow
Convolutional Neural Network
Recurrent Neural Network and LTSM
Transfer Learning
In this course, we will start from the very beginning and go all the way to the end of "Deep Learning" with examples.
Before we start this course, we will learn which environments we can be used for developing deep learning projects.
Why would you want to take this course?
Our answer is simple: The quality of teaching.
OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 1000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.
When you enroll, you will feel the OAK Academy`s seasoned developers' expertise. Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.
What is machine learning?
Machine learning describes systems that make predictions using a model trained on real-world data. For example, let's say we want to build a system that can identify if a cat is in a picture. We first assemble many pictures to train our machine learning model. During this training phase, we feed pictures into the model, along with information around whether they contain a cat. While training, the model learns patterns in the images that are the most closely associated with cats. This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat. In this particular example, we might use a neural network to learn these patterns, but machine learning can be much simpler than that. Even fitting a line to a set of observed data points, and using that line to make new predictions, counts as a machine learning model.
What is machine learning used for?
Machine learning is being applied to virtually every field today. That includes medical diagnoses, facial recognition, weather forecasts, image processing, and more. In any situation in which pattern recognition, prediction, and analysis are critical, machine learning can be of use. Machine learning is often a disruptive technology when applied to new industries and niches. Machine learning engineers can find new ways to apply machine learning technology to optimize and automate existing processes. With the right data, you can use machine learning technology to identify extremely complex patterns and yield highly accurate predictions.
Does machine learning require coding?
It's possible to use machine learning without coding, but building new systems generally requires code. For example, Amazon’s Rekognition service allows you to upload an image via a web browser, which then identifies objects in the image. This uses a pre-trained model, with no coding required. However, developing machine learning systems involves writing some Python code to train, tune, and deploy your models. It's hard to avoid writing code to pre-process the data feeding into your model. Most of the work done by a machine learning practitioner involves cleaning the data used to train the machine. They also perform “feature engineering” to find what data to use and how to prepare it for use in a machine learning model. Tools like AutoML and SageMaker automate the tuning of models. Often only a few lines of code can train a model and make predictions from it. An introductory understanding of Python will make you more effective in using machine learning systems.
What are the limitations of Python?
Python is a widely used, general-purpose programming language, but it has some limitations. Because Python is an interpreted, dynamically typed language, it is slow compared to a compiled, statically typed language like C. Therefore, Python is useful when speed is not that important. Python's dynamic type system also makes it use more memory than some other programming languages, so it is not suited to memory-intensive applications. The Python virtual engine that runs Python code runs single-threaded, making concurrency another limitation of the programming language. Though Python is popular for some types of game development, its higher memory and CPU usage limits its usage for high-quality 3D game development. That being said, computer hardware is getting better and better, and the speed and memory limitations of Python are getting less and less relevant making Python even more popular.
How is Python used?
Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks in the background. Many of the scripts that ship with Linux operating systems are Python scripts. Python is also a popular language for machine learning, data analytics, data visualization, and data science because its simple syntax makes it easy to quickly build real applications. You can use Python to create desktop applications. Many developers use it to write Linux desktop applications, and it is also an excellent choice for web and game development. Python web frameworks like Flask and Django are a popular choices for developing web applications. Recently, Python is also being used as a language for mobile development via the Kivy third-party library, although there are currently some drawbacks Python needs to overcome when it comes to mobile development.
What jobs use Python?
Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website and server deployments. Web developers use Python to build web applications, usually with one of Python's popular web frameworks like Flask or Django. Data scientists and data analysts use Python to build machine learning models, generate data visualizations, and analyze big data. Financial advisors and quants (quantitative analysts) use Python to predict the market and manage money. Data journalists use Python to sort through information and create stories. Machine learning engineers use Python to develop neural networks and artificial intelligent systems.
How do I learn Python on my own?
Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar with the syntax. But you only need to know a little bit about Python syntax to get started writing real code; you will pick up the rest as you go. Depending on the purpose of using it, you can then find a good Python tutorial, book, or course that will teach you the programming language by building a complete application that fits your goals. If you want to develop games, then learn Python game development. If you're going to build web applications, you can find many courses that can teach you that, too. Udemy’s online courses are a great place to start if you want to learn Python on your own.
What is data science?
We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover hidden patterns. This is where data science comes in. Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction. Data science seeks to find patterns in data and use those patterns to predict future data. It draws on machine learning to process large amounts of data, discover patterns, and predict trends. Data science includes preparing, analyzing, and processing data. It draws from many scientific fields, and as a science, it progresses by creating new algorithms to analyze data and validate current methods.
What does a data scientist do?
Data Scientists use machine learning to discover hidden patterns in large amounts of raw data to shed light on real problems. This requires several steps. First, they must identify a suitable problem. Next, they determine what data are needed to solve such a situation and figure out how to get the data. Once they obtain the data, they need to clean the data. The data may not be formatted correctly, it might have additional unnecessary data, it might be missing entries, or some data might be incorrect. Data Scientists must, therefore, make sure the data is clean before they analyze the data. To analyze the data, they use machine learning techniques to build models. Once they create a model, they test, refine, and finally put it into production.
What are the most popular coding languages for data science?
Python is the most popular programming language for data science. It is a universal language that has a lot of libraries available. It is also a good beginner language. R is also popular; however, it is more complex and designed for statistical analysis. It might be a good choice if you want to specialize in statistical analysis. You will want to know either Python or R and SQL. SQL is a query language designed for relational databases. Data scientists deal with large amounts of data, and they store a lot of that data in relational databases. Those are the three most-used programming languages. Other languages such as Java, C++, JavaScript, and Scala are also used, albeit less so. If you already have a background in those languages, you can explore the tools available in those languages. However, if you already know another programming language, you will likely be able to pick up Python very quickly.
How long does it take to become a data scientist?
This answer, of course, varies. The more time you devote to learning new skills, the faster you will learn. It will also depend on your starting place. If you already have a strong base in mathematics and statistics, you will have less to learn. If you have no background in statistics or advanced mathematics, you can still become a data scientist; it will just take a bit longer. Data science requires lifelong learning, so you will never really finish learning. A better question might be, "How can I gauge whether I know enough to become a data scientist?" Challenge yourself to complete data science projects using open data. The more you practice, the more you will learn, and the more confident you will become. Once you have several projects that you can point to as good examples of your skillset as a data scientist, you are ready to enter the field.
How can I learn data science on my own?
It is possible to learn data science on your own, as long as you stay focused and motivated. Luckily, there are a lot of online courses and boot camps available. Start by determining what interests you about data science. If you gravitate to visualizations, begin learning about them. Starting with something that excites you will motivate you to take that first step. If you are not sure where you want to start, try starting with learning Python. It is an excellent introduction to programming languages and will be useful as a data scientist. Begin by working through tutorials or Udemy courses on the topic of your choice. Once you have developed a base in the skills that interest you, it can help to talk with someone in the field. Find out what skills employers are looking for and continue to learn those skills. When learning on your own, setting practical learning goals can keep you motivated.
Does data science require coding?
The jury is still out on this one. Some people believe that it is possible to become a data scientist without knowing how to code, but others disagree. A lot of algorithms have been developed and optimized in the field. You could argue that it is more important to understand how to use the algorithms than how to code them yourself. As the field grows, more platforms are available that automate much of the process. However, as it stands now, employers are primarily looking for people who can code, and you need basic programming skills. The data scientist role is continuing to evolve, so that might not be true in the future. The best advice would be to find the path that fits your skill set.
What skills should a data scientist know?
A data scientist requires many skills. They need a strong understanding of statistical analysis and mathematics, which are essential pillars of data science. A good understanding of these concepts will help you understand the basic premises of data science. Familiarity with machine learning is also important. Machine learning is a valuable tool to find patterns in large data sets. To manage large data sets, data scientists must be familiar with databases. Structured query language (SQL) is a must-have skill for data scientists. However, nonrelational databases (NoSQL) are growing in popularity, so a greater understanding of database structures is beneficial. The dominant programming language in Data Science is Python — although R is also popular. A basis in at least one of these languages is a good starting point. Finally, to communicate findings, data scientists require knowledge of visualizations. Data visualizations allow them to share complex data in an accessible manner.
Is data science a good career?
The demand for data scientists is growing. We do not just have data scientists; we have data engineers, data administrators, and analytics managers. The jobs also generally pay well. This might make you wonder if it would be a promising career for you. A better understanding of the type of work a data scientist does can help you understand if it might be the path for you. First and foremost, you must think analytically. Data science is about gaining a more in-depth understanding of info through data. Do you fact-check information and enjoy diving into the statistics? Although the actual work may be quite technical, the findings still need to be communicated. Can you explain complex findings to someone who does not have a technical background? Many data scientists work in cross-functional teams and must share their results with people with very different backgrounds. If this sounds like a great work environment, then it might be a promising career for you.
Video and Audio Production Quality
All our videos are created/produced as high-quality video and audio to provide you with the best learning experience.
You will be,
Seeing clearly
Hearing clearly
Moving through the course without distractions
You'll also get:
Lifetime Access to The Course
Fast & Friendly Support in the Q&A section
Udemy Certificate of Completion Ready for Download
We offer full support, answering any questions.
If you are ready to learn the “Artificial intelligence with machine learning, deep learning” course.
Dive in now! See you in the course!
Who this course is for:
- Anyone who wants to start learning "Machine Learning"
- Anyone who needs a complete guide on how to start and continue their career with machine learning
- Anyone who needs a complete guide on how to start and continue their career with machine learning
- Students Interested in Beginning Data Science Applications in Python Environment
- People Wanting to Specialize in Anaconda Python Environment for Data Science and Scientific Computing
- Students Wanting to Learn the Application of Supervised Learning (Classification) on Real Data Using Python
- People who want to learn machine learning, deep learning, python
- People who want to learn artificial intelligence
- People who want to learn artificial intelligence with machine learning
- People who want to learn artificial intelligence with deep learning
- People who want to learn artificial intelligence with transfer learning, supervised learning
- People who want to learn artificial intelligence with machine learning, deep learning, transfer learning, supervised learning, unsupervised machine learning methods, ai
The Absolute Beginners Guide to Artificial Intelligence
Wednesday, March 5, 2025
Learn the fundamentals of AI including Machine & Deep Learning, Natural Linguistic Processing, Neural networks and more
Preview this Course
Description
Why Enroll in This Course?
Artificial Intelligence (AI) is transforming industries and shaping the future of technology. Whether you’re a business professional, student, entrepreneur, or simply curious about AI, this course will provide you with a solid foundation in AI concepts without requiring any prior knowledge or coding experience.
No coding required – Ideal for absolute beginners.
Understand AI fundamentals – Learn how AI, Machine Learning, and Deep Learning work.
Stay ahead of the curve – AI is revolutionizing every industry; gain the knowledge you need to stay competitive.
Engaging learning experience – A mix of lectures, real-world examples, and quizzes to reinforce your understanding.
What You’ll Learn
By the end of this course, you’ll have a strong grasp of AI fundamentals, including:
Foundations of AI
Machine Learning Basics
Deep learning & Neural networks
How AI makes decisions
AI in the real world
Who Should Take This Course?
This course is designed for anyone interested in learning about AI, including:
Beginners who want to explore AI without coding.
Business professionals who need to understand AI’s impact on their industry.
Entrepreneurs who want to leverage AI for innovation.
Students preparing for careers in technology, data science, or AI-related fields.
Start Your AI Journey Today!
Don’t miss the opportunity to understand AI’s impact and future possibilities. Whether you’re looking to advance your career, make informed decisions, or simply expand your knowledge, this course is the perfect place to start.
Enroll now and take your first step into the world of Artificial Intelligence!
Who this course is for:
- Beginners who want to explore AI without coding
- Business professionals who need to understand AI’s impact on their industry.
- Entrepreneurs who want to leverage AI for innovation
- Students preparing for careers in technology, data science, or AI-related fields
Python AI: Build Smart Assistants & Computer Vision Projects
Thursday, January 9, 2025
Create AI-powered assistants and develop real-time face detection and emotion recognition systems with Python.
Preview this Course
Description
In this comprehensive course, you will learn how to build your very own AI-powered assistant while mastering computer vision techniques. Starting from scratch, you'll gain hands-on experience in Python programming, which is essential for developing intelligent applications. The course covers the basics of building an AI assistant, including text-to-speech, speech recognition, and wake-up word functionality, all the way to advanced computer vision concepts like real-time face detection, face recognition, and emotion analysis. Whether you’re a beginner looking to explore AI and computer vision or an intermediate developer wanting to level up your skills, this course provides the perfect balance of theory and practical applications. You’ll work on exciting projects that integrate AI with computer vision, making it easy to apply your knowledge in real-world scenarios. By the end of the course, you will have developed several complete AI projects and a solid understanding of Python, AI, and computer vision technologies, which are in high demand across industries. You will also learn how to troubleshoot and optimize your AI models for better performance and accuracy. This course will provide you with the skills needed to build professional-level AI applications, setting you up for success in the rapidly growing AI and software development fields.
Who this course is for:
- Beginners eager to dive into Python programming and build AI assistants
- Aspiring developers wanting to explore computer vision and AI technologies
- Anyone interested in combining practical AI skills with real-world applications
Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT
Friday, September 6, 2024
Free Coupon Discount - Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT, Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!
BESTSELLER, 4.4 (11,781 ratings), Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, SuperDataScience Support, English [Auto-generated], French [Auto-generated], 9 more
PREVIEW THIS COURSE - GET COUPON CODE
Description
*** AS SEEN ON KICKSTARTER ***
Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:
How to start building AI with no previous coding experience using Python
How to merge AI with OpenAI Gym to learn as effectively as possible
How to optimize your AI to reach its maximum potential in the real world
Here is what you will get with this course:
1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.
2. Code templates – Plus, you’ll get downloadable Python code templates for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.
3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.
4. Real-world solutions – You’ll achieve your goal in not only 1 game but in 3. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.
5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT
Monday, July 8, 2024
Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT
Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!
PREVIEW THIS COURSE - GET COUPON CODE
What you'll learn
- Build 7 different AIs for 7 different applications
- Understand the theory behind Artificial Intelligence
- Master the State of the Art AI models
- Solve Real World Problems with AI
- Q-Learning
- Deep Q-Learning
- Deep Convolutional Q-Learning
- A3C (Asynchronous Advantage Actor-Critic)
- PPO (Proximal Policy Optimization)
- SAC (Soft Actor-Critic)
- LLMs
- Transformers
- Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
- NLP techniques for Chatbots: Tokenization and Padding
- Fine-Tuning an LLM with Knowledge Augmentation
- As Extras: DDPG, Full World Model, Evolution Strategies & Genetic Algorithms
Description
Welcome to Artificial Intelligence A-Z!
Learn key AI concepts with intuition lectures to get you quickly up to speed with all things AI and practice them by building 7 different AIs:
Build an AI with a Q-Learning model and train it to optimize warehouse flows in a Process Optimization case study.
Build an AI with a Deep Q-Learning model and train it to land on the moon.
Build an AI with a Deep Convolutional Q-Learning model and train it to play the game of Pac-Man.
Build an AI with an A3C (Asynchronous Advantage Actor-Critic) model and train it to fight Kung Fu.
Build an AI with a PPO (Proximal Policy Optimization) model and train it for a Self-Driving Car.
Build an AI with a SAC (Soft Actor-Critic) model and train it for a Self-Driving Car.
Build an AI by fine-tuning a powerful pre-trained LLM (Llama 2 by Meta) with Hugging Face and re-train it to chat with you about medical terms. Simply put, we build here an AI Doctor Chatbot.
But that's not all... Once you complete the course, you will get 3 extra AIs: DDPG, Full World Model, and Evolution Strategies & Genetic Algorithms. We build these AIs with ChatGPT for a Self-Driving Car and a Humanoid application. For each of these extra AIs you will get a long video lecture explaining the implementation, a mini PDF, and the Python code.
Besides, you will get a free 3-hour extra course on Generative AI and LLMs with Cloud Computing as a Prize for completing the course.
And last but not least, here is what you will get with this course:
1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.
2. Hassle-Free Coding and Code templates – We will build all our AIs in Google Colab, which means that we will have absolutely NO hassle installing libraries or packages because everything is already pre-installed in Google Colab notebooks. Plus, you’ll get downloadable Python code templates (in .py and .ipynb) for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.
3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in AI for much better results down the line.
4. Real-world solutions – You’ll achieve your goal in not only one AI model but in 5. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.
5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.
So, are you ready to embrace the fascinating world of AI?
Come join us, never stop learning, and enjoy AI!
Who this course is for:
- Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
Deep Reinforcement Learning 2.0
Friday, January 13, 2023
Free Coupon Discount - Deep Reinforcement Learning 2.0, The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG
Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team
Students also bought
- Natural Language Processing with Deep Learning in Python
- Recommender Systems and Deep Learning in Python
- Data Science: Natural Language Processing (NLP) in Python
- Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs
- The Complete Neural Networks Bootcamp: Theory, Applications
- Cutting-Edge AI: Deep Reinforcement Learning in Python
Preview this Udemy Course GET COUPON CODE
Description
Welcome to Deep Reinforcement Learning 2.0!
In this course, we will learn and implement a new incredibly smart AI model, called the Twin-Delayed DDPG, which combines state of the art techniques in Artificial Intelligence including continuous Double Deep Q-Learning, Policy Gradient, and Actor Critic. The model is so strong that for the first time in our courses, we are able to solve the most challenging virtual AI applications (training an ant/spider and a half humanoid to walk and run across a field).
To approach this model the right way, we structured the course in three parts:
Part 1: Fundamentals
In this part we will study all the fundamentals of Artificial Intelligence which will allow you to understand and master the AI of this course. These include Q-Learning, Deep Q-Learning, Policy Gradient, Actor-Critic and more.
Part 2: The Twin-Delayed DDPG Theory
We will study in depth the whole theory behind the model. You will clearly see the whole construction and training process of the AI through a series of clear visualization slides. Not only will you learn the theory in details, but also you will shape up a strong intuition of how the AI learns and works. The fundamentals in Part 1, combined to the very detailed theory of Part 2, will make this highly advanced model accessible to you, and you will eventually be one of the very few people who can master this model.
Part 3: The Twin-Delayed DDPG Implementation
We will implement the model from scratch, step by step, and through interactive sessions, a new feature of this course which will have you practice on many coding exercises while we implement the model. By doing them you will not follow passively the course but very actively, therefore allowing you to effectively improve your skills. And last but not least, we will do the whole implementation on Colaboratory, or Google Colab, which is a totally free and open source AI platform allowing you to code and train some AIs without having any packages to install on your machine. In other words, you can be 100% confident that you press the execute button, the AI will start to train and you will get the videos of the spider and humanoid running in the end.
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Machine Learning Practical Workout | 8 Real-World Projects
Monday, January 2, 2023
Free Coupon Discount - Machine Learning Practical Workout | 8 Real-World Projects, Build 8 Practical Projects and Go from Zero to Hero in Deep/Machine Learning, Artificial Neural Networks
Created by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, Mitchell Bouchard
Students also bought
- Natural Language Processing with Deep Learning in Python
- Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)
- Unsupervised Deep Learning in Python
- Recommender Systems and Deep Learning in Python
- Data Science: Natural Language Processing (NLP) in Python
- Ensemble Machine Learning in Python: Random Forest, AdaBoost
Preview this Udemy Course GET COUPON CODE
Description
"Deep Learning and Machine Learning are one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Machine/Deep Learning techniques are widely used in several sectors nowadays such as banking, healthcare, transportation and technology.
Machine learning is the study of algorithms that teach computers to learn from experience. Through experience (i.e.: more training data), computers can continuously improve their performance. Deep Learning is a subset of Machine learning that utilizes multi-layer Artificial Neural Networks. Deep Learning is inspired by the human brain and mimics the operation of biological neurons. A hierarchical, deep artificial neural network is formed by connecting multiple artificial neurons in a layered fashion. The more hidden layers added to the network, the more “deep” the network will be, the more complex nonlinear relationships that can be modeled. Deep learning is widely used in self-driving cars, face and speech recognition, and healthcare applications.
The purpose of this course is to provide students with knowledge of key aspects of deep and machine learning techniques in a practical, easy and fun way. The course provides students with practical hands-on experience in training deep and machine learning models using real-world dataset. This course covers several technique in a practical manner, the projects include but not limited to:
(1) Train Deep Learning techniques to perform image classification tasks.
(2) Develop prediction models to forecast future events such as future commodity prices using state of the art Facebook Prophet Time series.
(3) Develop Natural Language Processing Models to analyze customer reviews and identify spam/ham messages.
(4) Develop recommender systems such as Amazon and Netflix movie recommender systems.
The course is targeted towards students wanting to gain a fundamental understanding of Deep and machine learning models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master deep and machine learning models and can directly apply these skills to solve real world challenging problems."
100% Off Udemy Coupon . Free Udemy Courses . Online Classes
Master Artificial Intelligence 2022 : Build 6 AI Projects
Saturday, April 30, 2022
Master Artificial Intelligence 2022 : Build 6 AI Projects - Learn Artificial Intelligence with Python. Create Advanced Artificial Intelligence (AI) Applications with Python
Preview this Course
What you'll learn
- Machine Learning
- Deep Learning
- Natural Language Processing
- Artificial Neural Network
- Convolutional Neural Network
- Recurrent Neural Network
- Quizzes and exercises
- Understand the theory
- Build and train AI model
- Apply AI in business applications
- Build, train, deploy AI models in business
- Understand the concept of Explainable AI
Requirements
- For taking up this course you need to be enthusiastic and self confident.
- You need to have good knowledge of programming and basic mathematical skills.
- For taking up this course you need to be enthusiastic and self confident.
- A willingness to learn and practice.
Description
Are you ready to master Artificial Intelligence skills?
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. As technologies such as AI continue to grow,
they will have a great impact on our quality of life.
Artificial intelligence (AI) is one of the top tech fields to be in right now!
Financial institutions, legal institutions, media companies, and insurance companies are all figuring out ways to use artificial intelligence (ai) to their advantage. From fraud detection to writing news stories with natural language processing(NLP) and reviewing law briefs, AI’s reach is extensive.
If you want to build super-powerful applications in artificial intelligence(ai).
Then, you are at the right place.
This course will provide you with in-depth knowledge on a very hot topic i.e., Artificial Intelligence(AI).
The purpose of this course is to provide you with knowledge of key aspects of modern AI without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.
This course will cover the following topics:-
1. Natural Language Processing (NLP).
2. Artificial Neural Network (ANN).
3. Convolutional Neural Network (CNN).
4. Recurrent Neural Network. (RCN)
5. Machine Learning (ML).
6. Deep Learning (DL).
This course will take you through the basics to an advanced level in all the mentioned four topics.
After taking this course, you will be confident enough to work independently on any projects on these topics.
There are lots and lots of exercises for you to practice In this Python Data Science Course and also a 5 Bonus Data Science Project "Sentiment Analysis", "Drug Prescription", "Detecting Pneumonia from X-rays", "Stock Market Prediction", "Fruits Recognition" and "Face emotion Recognition".
In this Sentiment Analysis project, you will learn how to Extract and Scrap Data from Social Media Websites and Extract out Beneficial Information from these Data for Driving Huge Business Insights.
In this Drug Prescription project, you will learn how to Deal with Data having Textual Features, you will also learn NLP Techniques to transform and Process the Data to find out Important Insights.
In this Detecting Pneumonia from X-rays project, you will learn how to solve Image Classification Tasks using Deep Neural Networks such as ResNet which is a High Level CNN Architectures.
In this Stock Market Prediction project, you will learn to analyze and the Stock Market Prices using Time Series Forecasting, Advanced Deep Learning Models and different Statistical features.
In this Fruits Recognition project, you will learn how to solve a complicated Image Classification Task with Multiple Classes using various Deep Learning Architectures and Compare the Result.
In this Face Expression Recognizer project, you will learn to use Computer Vision Techniques to detect Human Emotions such as Angry, Sad, Happy, Disgust, Fear etc. to build a Facial Emotion Detector.
Instructor Support - Quick Instructor Support for any queries.
I'm looking forward to see you in the course!
You will have access to all the resources used in this course.
Who this course is for:
- This course is for everyone who wants to master AI skills.
- This course is for students who have already good knowledge of machine learning and have good programming skills.
- Job-seekers, Software Engineers and Data Scientists who want to level up their career
- Students and professionals who want to improve the training capabilities
- Machine Learning Engineer
- Just Passion for Learning
- Everyone who wants to improve their Python programming skills
- Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
Artificial Intelligence Expert Course + Live Class
Monday, April 25, 2022
Artificial Intelligence Expert Course + Live Class
A breathtaking course in 2022 that teaches new-age Artificial Intelligence (AI) Technologies and Tools
Preview this Course
What you'll learn
- Secretive Machine Learning Artificial Intelligence tools
- Secretive Research based Artificial Intelligence tools
- Secretive Digital Marketing Artificial Intelligence tools
- Secretive Business related Artificial Intelligence tools
- Secretive Notetaking Artificial Intelligence tools
- Secretive Video Creation Artificial Intelligence tools
- Secretive Analytics based Artificial Intelligence tools
- Secretive Graphic Design Artificial Intelligence tools
- Secretive Deep Learning Artificial Intelligence tools
- Secretive Voice Cloning Artificial Intelligence tools
- Secretive Mind Cloning Artificial Intelligence tools
- Secretive Virtual Reality or VR Artificial Intelligence tools
- Secretive Customer Support Artificial Intelligence tools
- Secretive Misc. Artificial Intelligence tools of 2022
- Secretive and Futuristic Programming Artificial Intelligence tools
- Secretive Entertainment or Game type Artificial Intelligence tools
- Secretive Augmented Reality or AR Artificial Intelligence tools
- Artificial General Intelligence (AGI) - Incredible Research Findings
- Learn how to prepare your business for the Artificial Intelligence Revolution
- Artificial Intelligence (AI) Trends for Social Media
- Learn about the concept of whether Robots can teach or not.
- Learn how to find your ideal career in the field of Artificial Intelligence (AI).
- Concepts of Computer Vision: Fundamentals
Requirements
- Several Artificial Intelligence coding tools will be taught in the course. Most of the tools will be free and also paid alternatives will be covered. You can choose the best tools according to your requirement with the correct features during usage.
Description
Welcome to experience a mind-blowing "Artificial Intelligence Expert Course" in 2022.
Artificial Intelligence Expert Course: Platinum Edition - The course has now launched.
Artificial Intelligence (AI) seems to be a unique technology for making a machine, a robot fully autonomous. AI is an analysis of how the machine is thinking, studying, determining, and functioning when it is trying to solve problems.
These kinds of problems are present in all fields, the most emerging ones, and even beyond. The aim of Artificial Intelligence is to enhance machine functions relating to human knowledge, such as reasoning, learning, and problems along with the ability to manipulate things. For example, virtual assistants or chatbots offer expert advice. Smart robots or robot advisors will provide instant research or findings in the fields of finance, insurance, law, the media, and journalism, and medical diagnosis and support will be provided by AI software on the health front. Other advantages include increasing productivity dramatically in research and development programs by reducing time to the market, enhancing the transport and supply chain networks and improving governance by improved decision-making processes etc.
Artificial Intelligence technology is aiding the following prominent fields for 2022 and many others:
Website Creation - Artificial Intelligence tools can help to create websites and landing pages in merely minutes.
App Creation - Artificial Intelligence tools can help to automate the whole concept of creating apps.
Natural Language Processing (NLP) − This process is simulating the actual interaction with the computer that understands natural language spoken by humans.
Expert Systems − Learners and users will be provided with guided information and advice on the computer or software.
Vision Systems − Artificial Intelligence (AI) systems in 2022 can understand, explain and describe the computer's visual input to the ultimate core.
Spoken Word or Speech Recognition − Many Artificial Intelligence (AI) based speech recognition systems are capable of listening, voicing and recognizing the user input - i.e. when a person speaks with them. Alexa, Siri and Google's assistant, are examples of this function.
Machine Learning - Artificial Intelligence (AI) can help users to create and experiment with machine learning models and build data science applications in a flash.
Video Creation - Artificial Intelligence (AI) can help to automate video production and cut high costs of hiring resources and teams as everything is taken care of in the cloud.
Python and Coding tools - Artificial Intelligence (AI) can help to automate writing lakhs of lines of code in python and even Java or PHP in minutes without the need for a human coder or even someone who will debug the code. Everything is automated in the concept of AI-powered programming.
This mind-blowing exhaustive course focusing on "Artificial Intelligence Expert Course: Platinum Edition" taught by Digital Marketing Legend Srinidhi Ranganathan and Civil MasterMind Saranya Srinidhi will change your perspective on the concept of Artificial Intelligence forever to rely on AI tools of the future for your needs. We will cover 100's of Artificial Intelligence (AI) tools that are highly popular in the following fields that include: Machine Learning, Deep Learning, Digital Marketing, Research, Analytics, Voice-cloning, Mind-Cloning, Video Creation, Virtual Reality (VR) based Artificial Intelligence tools etc. As you learn these AI tools you will understand that Artificial Intelligence has so much evolved in the last 2 to 5 years. You will also see the growth of the emergence of Artificial Intelligence (AI) tools across industries that have exploded and its impact on business and society that is emerging at a quick pace. In this incredible journey, you will also encounter businesses that are pushing the limits of automation, search and social media. As you slowly realize that with the brain of a computer, AI would potentially automate control in such sectors as self-employed vehicles and non-manned drones, you will be left spellbound.
"Artificial Intelligence (AI) will not only reduce costs by automating processes but also skyrocket revenues by helping startups and corporates introduce new product and service categories at the fastest speed ever imagined with limited resources."
But, will the jobs die as automation takes over? Will AI will surpass human intelligence in 2022, itself? The answer to these questions is a "No".
The development and eventual growth in AI apps helping in productivity will provide workers with a range of opportunities to improve their skills and concentrate on creative aspects. Stating additional forecasts, disruptive market trends are highly likely to occur in the AI Expansion period (i.e. 2025-2030), the opportunity for employment would require a high degree of personalization, innovation or ability tasks which will still require a person to perform them (even though the AI robotic tools have actually speeded up the process). These occupations or technologies are difficult to imagine at this stage, yet these occupations will rapidly increase as new specialization is required when the demand would kick in. The time is coming soon for a global Artificial Intelligence (AI) revolution to strongly emerge.
Okay. Let's start learning and go on an adventure in Artificial Intelligence. Enrol Now and I will see you inside. Let's rock this world with learning secretive tools. Don't waste any more time.
Special Note: Several Artificial Intelligence (AI) coding tools will be taught in the course. Most of the tools will be free and also paid alternatives will be covered. You can choose the best tools according to your requirements with the correct features during usage.
IMPORTANT:
Regarding the Live Group Q&A Session:
Students who have completed every lesson in the course will also get access to a free live online group Q&A session of 1 hour with Digital Marketing Legend "Srinidhi Ranganathan". You can clarify all your doubts there. Srinidhi will also showcase your career paths in Futuristic AI, and provide you with a full walkthrough of what you learned along with tips on how to improvise or implement the stuff taught.
Who this course is for:
- Beginner students who want to learn new-age Artificial Intelligence tools to take their career ahead to new heights of success
- Digital Marketing enthusiasts who wish to learn Artificial Intelligence technology tools
- Startup founders who wish to learn Artificial Intelligence tools in 2022
- Passionate students and learners who want to put a ding in the universe after learning Artificial Intelligence tools and implement those tools in their business and job
- Artificial Intelligence trainers who want to discover new technologies that are world changing in every aspect
- Research specialists, Machine Learning enthusiasts and Data Science Students who want to learn incredible tools and technologies in the field of Artificial Intelligence
- Virtual Reality or gaming enthusiasts who want to see something new to experiment on Artificial Intelligence technology
- Anyone who is interested to learn Artificial Intelligence tools that will help them all the time in their business, career or college
The Beginner's Guide to Artificial Intelligence in Unity.
Thursday, April 7, 2022
The Beginner's Guide to Artificial Intelligence in Unity. - A practical guide to programming non-player characters for games.
- Created by Penny de Byl, Penny @Holistic3D.com
- English, Portuguese [Auto]
What you'll learn
- Design and program NPCs with C# in Unity
- Explain how AI is applied in computer games
- Implement AI-related Unity Asset plugins into existing projects
- Work with a variety of AI techniques for developing navigation and decision making abilities in NPCs
Description
Do your non-player characters lack drive and ambition? Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you. Join Penny as she explains, demonstrates and assists you in creating your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.
In this course, Penny reveals the most popular AI techniques used for creating believable character behaviour in games using her internationally acclaimed teaching style and knowledge from over 25 years working with games, graphics and having written two award winning books on games AI. Throughout, you will follow along with hands-on workshops designed to teach you about the fundamental AI techniques used in today's games. You'll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.
Learn how to program and work with:
vectors
waypoints
navmeshes
the A* algorithm
crowds
flocks
animated characters
vehicles
Contents and Overview
The course begins with a detailed examination of vector mathematics that sits at the very heart of programming the movement of NPCs. Following this, systems of waypoints will be used to move characters around in an environment before examining the Unity waypoint system for car racing with AI controlled cars. This leads into an investigation of graph theory and the A* algorithm before we apply these principles to developing navmeshes and developing NPCs who can find their way around a game environment. Before an aquarium is programmed complete with autonomous schooling fish, crowds of people will be examined from the recreation of sidewalk traffic, to groups of people fleeing from danger. Having examined the differing ways to move NPCs around in a game environment, their thinking abilities will be discussed with full explanations and more hands-on workshops using finite state machines and behaviour trees.
The follow-along workshops included in the course come with starter Unity asset files and projects complete with solutions. Throughout, there are also quizzes and challenge exercises to reinforce your learning and guide you to express your newfound knowledge.
At the completion of this course you will have gained a broad understanding of what AI is in games, how it works and how you can use it in your own projects. It will equip you with a toolset to examine any of the techniques presented in more depth to take your game environments to the next level.
What students are saying about this course:
This has been my favourite Udemy-Unity course so far. It took me from literally 0% knowledge of how game AI is achieved, and took me to a whole new level. Waypoints, pathfinding, state machines, etc etc etc are all covered in-depth and will reveal the magic (spoiler alert: it isn't magic) behind making your computer characters seem like they really have a mind of their own.
Oh My God. I love her way of teaching things. I haven’t finished this course yet. But all i can say is that it is another brilliant course from her. Artificial intelligence by itself is a tricky thing to do. And before starting this course i never thought that i will understand anything in it. But i was wrong. With her style of teaching, you will learn how to move your characters in an ”intelligent“ way. This course is perfectly sliced and the pace is wonderful.
Who this course is for:
Anyone interested in learning how to program their own non-player characters (NPCs).
Anyone interested in seeing how artificial intelligence is applied in computer games.
Subscribe to:
Posts (Atom)