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Free Coupon Discount - Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning | Created by 365 Careers, 365 Careers Team

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Description
The Problem

Data scientist is one of the best suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.  

However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.

And how can you do that?

Universities have been slow at creating specialized data science programs. (not to mention that the ones that exist are very expensive and time consuming)

Most online courses focus on a specific topic and it is difficult to understand how the skill they teach fit in the complete picture

The Solution

Data science is a multidisciplinary field. It encompasses a wide range of topics.

Understanding of the data science field and the type of analysis carried out

Mathematics

Statistics

Python

Applying advanced statistical techniques in Python

Data Visualization

Machine Learning

Deep Learning

Each of these topics builds on the previous ones. And you risk getting lost along the way if you don’t acquire these skills in the right order. For example, one would struggle in the application of Machine Learning techniques before understanding the underlying Mathematics. Or, it can be overwhelming to study regression analysis in Python before knowing what a regression is.

So, in an effort to create the most effective, time-efficient, and structured data science training available online, we created The Data Science Course 2020.

We believe this is the first training program that solves the biggest challenge to entering the data science field – having all the necessary resources in one place.

Moreover, our focus is to teach topics that flow smoothly and complement each other. The course teaches you everything you need to know to become a data scientist at a fraction of the cost of traditional programs (not to mention the amount of time you will save).

The Skills

   1. Intro to Data and Data Science

Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean?  

Why learn it? As a candidate data scientist, you must understand the ins and outs of each of these areas and recognise the appropriate approach to solving a problem. This ‘Intro to data and data science’ will give you a comprehensive look at all these buzzwords and where they fit in the realm of data science.

   2. Mathematics

Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail.

We take a detailed look specifically at calculus and linear algebra as they are the subfields data science relies on.

Why learn it?

Calculus and linear algebra are essential for programming in data science. If you want to understand advanced machine learning algorithms, then you need these skills in your arsenal.

   3. Statistics

You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist.

Why learn it?

This course doesn’t just give you the tools you need but teaches you how to use them. Statistics trains you to think like a scientist.

   4. Python

Python is a relatively new programming language and, unlike R, it is a general-purpose programming language. You can do anything with it! Web applications, computer games and data science are among many of its capabilities. That’s why, in a short space of time, it has managed to disrupt many disciplines. Extremely powerful libraries have been developed to enable data manipulation, transformation, and visualisation. Where Python really shines however, is when it deals with machine and deep learning.

Why learn it?

When it comes to developing, implementing, and deploying machine learning models through powerful frameworks such as scikit-learn, TensorFlow, etc, Python is a must have programming language.

   5. Tableau

Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert story teller using the leading visualisation software in business intelligence and data science.

Why learn it?

A data scientist relies on business intelligence tools like Tableau to communicate complex results to non-technical decision makers.

   6. Advanced Statistics

Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail.

Why learn it?

Data science is all about predictive modelling and you can become an expert in these methods through this ‘advance statistics’ section.

   7. Machine Learning

The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow.

Why learn it?

Machine learning is everywhere. Companies like Facebook, Google, and Amazon have been using machines that can learn on their own for years. Now is the time for you to control the machines.

***What you get***

A $1250 data science training program

Active Q&A support

All the knowledge to get hired as a data scientist

A community of data science learners

A certificate of completion

Access to future updates

Solve real-life business cases that will get you the job

You will become a data scientist from scratch

We are happy to offer an unconditional 30-day money back in full guarantee. No risk for you. The content of the course is excellent, and this is a no-brainer for us, as we are certain you will love it.

Why wait? Every day is a missed opportunity.

Click the “Buy Now” button and become a part of our data scientist program today.



Who this course is for:
You should take this course if you want to become a Data Scientist 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

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Free Coupon Discount - Manage Finance Data with Python & Pandas: Unique Masterclass, Analyze Stocks with Pandas, Numpy, Seaborn & Plotly. Create, analyze & optimize Index & Portfolios (CAPM, Alpha, Beta) | Created by Alexander Hagmann

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Description
+++++ Updated to most recent Pandas Version 0.25.3 (Oct 2019) and ready for 2020 +++++



The Finance and Investment Industry is experiencing a dramatic change driven by ever increasing processing power & connectivity and the introduction of powerful Machine Learning tools. The Finance and Investment Industry more and more shifts from a math/formula-based business to a data-driven business.



What can you do to keep pace?

No matter if you want to dive deep into Machine Learning, or if you simply want to increase productivity at work when handling Financial Data, there is the very first and most important step: Leave Excel behind and manage your Financial Data with Python and Pandas!

Pandas is the Excel for Python and learning Pandas from scratch is almost as easy as learning Excel. Pandas seems to be more complex at a first glance, as it simply offers so much more functionalities. The workflows you are used to do with Excel can be done with Pandas more efficiently. Pandas is a high-level coding library where all the hardcore coding stuff with dozens of coding lines are running automatically in the background. Pandas operations are typically done in one line of code! However, it is important to learn and master Pandas in a way that

you understand what is going on

you are aware of the pitfalls (Don´ts)

you know best practices (Dos)



MANAGE FINANCE DATA WITH PYTHON & PANDAS best prepares you to master the new challenges and to stay ahead of your peers, fellows and competitors! Coding with Python/Pandas is one of the most in-Demand skills in Finance.

This course is one of the most practical courses on Udemy with 200 Coding Exercises and a Final Project. You are free to select your individual level of difficulty. If you have no experience with Pandas at all, Part 1 will teach you all essentials (From Zero to Hero).

Part 2 - The Core of this Course

Import Financial Data from Free Web Sources, Excel- and CSV-Files

Calculate Risk, Return and Correlation of Stocks, Indexes and Portfolios

Calculate simple Returns, log Returns and annualized Returns & Risk

Create your own customized Financial Index (price-weighted vs. equal-weighted vs. value-weighted)

Understand the difference between Price Return and Total Return

Create, analyze and optimize Stock Portfolios

Calculate Sharpe Ratio, Systematic Risk, Unsystematic Risk, Beta and Alpha for Stocks, Indexes and Portfolios

Understand Modern Portfolio Theory, Risk Diversification and the Capital Asset Pricing Model (CAPM)

Forward-looking Mean-Variance Optimization (MVO) and its pitfalls

Get exclusive insight how MVO is used in Real World (and why it is NOT used in many cases) -> get beyond Investments 101 level!

Calculate Rolling Statistics (e.g. Simple Moving Averages) and aggregate, visualize and report Financial Performance

Create Interactive Charts with Technical Indicators (SMA, Candle Stick, Bollinger Bands etc.)

Part 3 - Capstone Project

Step into the Financial Analyst / Advisor Role and give advice on a Client´s Portfolio (Final Project Challenge).

Apply and master what you have learned before!

Part 4

Some advanced topics on handling Time Series Data with Pandas.

Appendix

You struggle with some basic Python / Numpy concepts? Here is all you need to know, if you are completely new to Python!



Why you should listen to me...

In my career, I have built an extensive level of expertise and experience in both areas:  Finance and Coding

Finance:

7 years experience in the Finance and Investment Industry...

...where I held various quantitative & strategic positions.

MSc in Finance

Passed all three CFA Exams (currently no active member of the CFA Institute)

Python & Pandas:

I led a company-wide transformation from Excel to Python/Pandas

Code, models and workflows are Real World Project - proven

Instructor of the highest-rated and most trending general Course on Pandas



What are you waiting for? Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.

Looking Forward to seeing you in the Course!

Who this course is for:
Investment & Finance Professionals who want to transition from Excel into Python to boost their careers and working efficiency.
(Finance) Students and Researchers who need to handle large datasets and reached the limits of Excel.
Data Scientists who want to improve their Data Handling/Manipulation skills (in particular for Time Series Data)
Everyone who want to step into (Financial) Data Science. Pandas is Key to everything.
Everyone curious about how Financial Performance is measured and how (Stock) Indexes and Portfolios are created, analyzed, visualized and optimized. It´s the easiest way to understand the concepts with data examples rather than theories and formulas.

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Free Coupon Discount - Move beyond BASIC reports and learn data ANALYSIS. Learn to easily turn data into information, insight and intelligence | Created by Ian Littlejohn

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Description
Recent reviews:

"Yes the course was absolutely good. Somebody who want to have a quick grasp or learn on more if not most of the key analysis techniques then this the place."

"This course was very knowledgeable for me. Along with data analysis, I have also progressed from beginner to advanced stage in MS Excel. The speciality of this course is that it was a very systematically organized and also consistently progressing through the chapters with hands-on practical experience! I enjoyed this course!"

"Excellent explanation and Practice activity.It was simple, crisp and clear."

In this course you will learn the BEST techniques and tools for turning data into MEANINGFUL analysis using Excel

This course is lead by Ian Littlejohn - an international trainer, consultant and data analyst with over 50 000 enrollments on Udemy and consistently high reviews.  Ian specialises in teaching data analysis techniques, Excel Pivot Tables, Power Pivot, Microsoft Power BI and Google Data Studio.

**** Life time access to course materials and practice activities.  100% money back guarantee ****

The Complete Introduction to Business Data Analysis teaches you how to apply different methods of data analysis to turn your data into new insight and intelligence.

The ability to ask questions of your data is a powerful competitive advantage, resulting in new income streams, better decision making and improved productivity.  A recent McKinsey Consulting report has identified that data analysis is one of the most important skills required in the American economy at the current time.

During the course you will understand why the form of analysis is important and also provide examples of analysis using Excel 2010.

The following methods of analysis are included:

Comparison Analysis

Trend Analysis

Ranking Analysis

Interactive Dashboards

Contribution Analysis

Variance Analysis

Pareto Analysis

Frequency Analysis

Correlations

The Complete Introduction to Business Data Analysis is designed for all business professionals who want to take their ability to turn data into information to the next level. If you are an Excel user then you will want to learn the easy to use techniques that are taught in this course.

This course is presented using Excel in Office 365.  However the course is also suitable for:

Excel 2013

Excel 2016

Excel 2019

Please note that this course does not include any complicated formulas, VBA or macros.  The course utilizes drag and drop techniques to create the majority of the different data analysis techniques.

Who this course is for:
All Business people who want to turn data into information
Excel users who want to take their reporting and analysis to the next level
Students who want to learn powerful methods of data analysis

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Free Coupon Discount - Microsoft Excel - Advanced Excel Formulas & Functions, Master 75+ Excel formulas with hands-on demos from a best-selling Microsoft Excel instructor (Excel '07 - Excel

Bestseller
Created by Maven Analytics Chris Dutton

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Description
See why this is one of the TOP-RATED Excel courses on Udemy:
"One of the best Excel courses I've ever taken. You can see through his videos how passionate he is about Excel. Thanks for this awesome course, and count me in for the next ones!"
-Julio Garcia
"This is an exceptionally valuable course. The information is vital with examples of best practices from a true Excel expert. Chris Dutton can teach!"
-Barbara S.
"Chris Dutton is an EXPERT in Excel. He makes comprehensible to the student the complex (sometimes super-complex) nature of the formulas he uses. Everything that is written at the course description, although it may seem pure marketing and publicity at first glance, is indeed true. If I could rate it higher I definitively would. THANKS Chris!"
-Bruno Ricardo Silva Pinho
__________

FULL COURSE DESCRIPTION:
__________
It's time to show Excel who's boss. Whether you're starting from square one or aspiring to become an absolute Excel power user, you've come to the right place.
This course will give you a deep understanding of the advanced Excel formulas and functions that transform Excel from a basic spreadsheet program into a dynamic and powerful analytics tool. While most Excel courses focus on simply what each formula does, I teach through hands-on, contextual examples designed to showcase why these formulas are awesome and how they can be applied in a number of ways. I will not train you to regurgitate functions and formula syntax; I will teach you how to THINK like Excel.
__________
By the end of the course you'll be writing robust, elegant formulas and functions from scratch, allowing you to:
Easily build dynamic tools & Excel dashboards to filter, display and analyze your data
Go rogue and design your own formula-based Excel formatting rules
Join datasets from multiple sources with Excel's LOOKUP, INDEX & MATCH functions
Pull real-time data from APIs directly into Excel (weather, stock quotes, directions, etc.)
Manipulate dates, times, text, and arrays
Automate tedious and time-consuming tasks using cell formulas and functions in Excel (no VBA required!)
__________
We'll dive into a broad range of Excel formulas & functions, including:
Lookup/Reference functions
Statistical functions
Formula-based formatting
Date & Time functions
Logical operators
Array formulas
Text functions
INDIRECT & HYPERLINK
Web scraping with WEBSERVICE & FILTERXML
__________
What gives you the right to teach this class? Can't I just Google this stuff?
I have a genuine passion for Excel that most people reserve for things like kittens, ice cream, and significant others. The only thing I love more than learning Excel is teaching it, and as the founder of Excel Maven and Maven Analytics I've been lucky enough to teach Excel to 200,000+ students across 180+ countries. My teaching style is conversational, authentic and to the point, and I will always communicate complex concepts in a framework that is clear and easy to comprehend.
As a full-time analytics consultant and Excel instructor, I cut my teeth using Excel to solve real-world business problems and develop award-winning analytics & data visualization tools for Fortune 500 companies. If you care about creds, I'm a card-carrying MOS Certified Excel Expert and my work has been featured by Microsoft and the New York Times. Ok so I don't actually carry the card, but you get the idea.
If you're looking for the ONE course with all of the advanced Excel formulas and functions that you need to know to become an absolute Excel ninja, you've found it.
See you in there!
-Chris (Founder, Maven Analytics)
__________
Most students in this course enroll in our full EXCEL LEARNING PATH, designed to help you build a deep, expert-level Excel skill set:
Advanced Excel Formulas & Functions (you are here)
Data Visualization with Excel Charts & Graphs
Data Analysis with Excel PivotTables
Excel Power Query, Power Pivot & DAX
Excel Pro Tips for Power Users
Looking for the full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, and Tableau courses!
*NOTE: Full course includes downloadable resources and Excel project files, homework and course quizzes, lifetime access and a 30-day money-back guarantee. Most lectures compatible with Excel 2007, Excel 2010, Excel 2013, Excel 2016, Excel 2019 or Office 365.

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Free Coupon Discount - The Data Science & Machine Learning Bootcamp in Python, Learn Python for Data Science,NumPy,Pandas,Matplotlib,Seaborn,Scikit-learn, Dask,LightGBM,XGBoost,CatBoost and much more

Created by Derrick Mwiti, Namespace Labs, English [Auto]

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Description
In this course, you'll learn how to get started in data science. You don't need any prior knowledge in programming. We'll teach you the Python basics you need to get started.  Here are the items we'll cover in this course
The Data Science Process
Python for Data Science
NumPy for Numerical Computation
Pandas for Data Manipulation
Matplotlib for Visualization
Seaborn for Beautiful Visuals
Plotly for Interactive Visuals
Introduction to Machine Learning
Dask for Big Data
Deep Learning & Next Steps
For the machine learning section here are some items we'll cover :
How Algorithms Work
Advantages & Disadvantages of Various Algorithms
Feature Importances
Metrics
Cross-Validation
Fighting Overfitting
Hyperparameter Tuning
Handling Imbalanced Data

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