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2021-01-11 07:53:28
30-Day Money-Back Guarantee
Development Data Science Data Analysis

The Data Science Course 2021: Complete Data Science Bootcamp

Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning
Bestseller
Rating: 4.6 out of 54.6 (87,359 ratings)
372,041 students
Created by 365 Careers, 365 Careers Team
Last updated 1/2021
English
English [Auto], French [Auto], 
30-Day Money-Back Guarantee

What you'll learn

  • The course provides the entire toolbox you need to become a data scientist
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Impress interviewers by showing an understanding of the data science field
  • Learn how to pre-process data
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Start coding in Python and learn how to use it for statistical analysis
  • Perform linear and logistic regressions in Python
  • Carry out cluster and factor analysis
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Apply your skills to real-life business cases
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Unfold the power of deep neural networks
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
Curated for the Udemy for Business collection

Course content

63 sections • 476 lectures • 28h 54m total length

  • Preview05:05
  • Preview03:34
  • Download All Resources and Important FAQ
    10:42

  • Data Science and Business Buzzwords: Why are there so Many?
    Preview05:21
  • Data Science and Business Buzzwords: Why are there so Many?
    1 question
  • What is the difference between Analysis and Analytics
    03:50
  • What is the difference between Analysis and Analytics
    1 question
  • Business Analytics, Data Analytics, and Data Science: An Introduction
    Preview08:26
  • Business Analytics, Data Analytics, and Data Science: An Introduction
    3 questions
  • Continuing with BI, ML, and AI
    09:31
  • Continuing with BI, ML, and AI
    2 questions
  • A Breakdown of our Data Science Infographic
    04:03
  • A Breakdown of our Data Science Infographic
    1 question

  • Applying Traditional Data, Big Data, BI, Traditional Data Science and ML
    07:19
  • Applying Traditional Data, Big Data, BI, Traditional Data Science and ML
    1 question

  • The Reason Behind These Disciplines
    04:44
  • The Reason Behind These Disciplines
    1 question

  • Techniques for Working with Traditional Data
    08:13
  • Techniques for Working with Traditional Data
    1 question
  • Real Life Examples of Traditional Data
    01:44
  • Techniques for Working with Big Data
    04:26
  • Techniques for Working with Big Data
    1 question
  • Real Life Examples of Big Data
    01:32
  • Business Intelligence (BI) Techniques
    06:45
  • Business Intelligence (BI) Techniques
    4 questions
  • Real Life Examples of Business Intelligence (BI)
    01:42
  • Techniques for Working with Traditional Methods
    09:08
  • Techniques for Working with Traditional Methods
    4 questions
  • Real Life Examples of Traditional Methods
    02:45
  • Machine Learning (ML) Techniques
    06:55
  • Machine Learning (ML) Techniques
    2 questions
  • Types of Machine Learning
    08:13
  • Types of Machine Learning
    2 questions
  • Real Life Examples of Machine Learning (ML)
    02:11
  • Real Life Examples of Machine Learning (ML)
    5 questions

  • Necessary Programming Languages and Software Used in Data Science
    05:51
  • Necessary Programming Languages and Software Used in Data Science
    4 questions

  • Finding the Job - What to Expect and What to Look for
    03:29
  • Finding the Job - What to Expect and What to Look for
    1 question

  • Debunking Common Misconceptions
    04:10
  • Debunking Common Misconceptions
    1 question

  • The Basic Probability Formula
    07:09
  • The Basic Probability Formula
    3 questions
  • Computing Expected Values
    05:29
  • Computing Expected Values
    3 questions
  • Frequency
    05:00
  • Frequency
    3 questions
  • Events and Their Complements
    05:26
  • Events and Their Complements
    3 questions

  • Fundamentals of Combinatorics
    01:04
  • Fundamentals of Combinatorics
    1 question
  • Permutations and How to Use Them
    03:21
  • Permutations and How to Use Them
    2 questions
  • Simple Operations with Factorials
    03:35
  • Simple Operations with Factorials
    3 questions
  • Solving Variations with Repetition
    02:59
  • Solving Variations with Repetition
    3 questions
  • Solving Variations without Repetition
    03:48
  • Solving Variations without Repetition
    3 questions
  • Solving Combinations
    04:51
  • Solving Combinations
    4 questions
  • Symmetry of Combinations
    03:26
  • Symmetry of Combinations
    1 question
  • Solving Combinations with Separate Sample Spaces
    02:52
  • Solving Combinations with Separate Sample Spaces
    1 question
  • Combinatorics in Real-Life: The Lottery
    03:12
  • Combinatorics in Real-Life: The Lottery
    1 question
  • A Recap of Combinatorics
    02:55
  • A Practical Example of Combinatorics
    10:53

Requirements

  • No prior experience is required. We will start from the very basics
  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Microsoft Excel 2003, 2010, 2013, 2016, or 365

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 2021.  

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

Featured review

Janaki Ballav Mohapatra
Janaki Ballav Mohapatra
24 courses
5 reviews
Rating: 5.0 out of 511 months ago
AS always, 365 careers is fantastic. I loved the Deep Nets part mostly. However, some other popular Machine Learning techniques such as Random Forest Classification/Regression and Support Vector Machines/Regression should have been addressed. Having said that, it is still a very good course which covers almost everything. Thank you 365 team, You all are simply the best. Janaki Mohapatra, India

Instructors

365 Careers
Creating opportunities for Business & Finance students
365 Careers
  • 4.5 Instructor Rating
  • 389,916 Reviews
  • 1,336,145 Students
  • 70 Courses

365 Careers is the #1 best-selling provider of finance courses on Udemy. The company’s courses have been taken by more than 1,000,000 students in 210 countries. People working at world-class firms like Apple, PayPal, and Citibank have completed 365 Careers trainings.  

Currently, the firm focuses on the following topics on Udemy:  

1) Finance – Finance fundamentals, Financial modeling in Excel, Valuation, Accounting, Capital budgeting, Financial statement analysis (FSA), Investment banking (IB), Leveraged buyout (LBO), Financial planning and analysis (FP&A), Corporate budgeting, applying Python for Finance, Tesla valuation case study, CFA, ACCA, and CPA

2) Data science – Statistics, Mathematics, Probability, SQL, Python programming, Python for Finance, Business Intelligence, R, Machine Learning, TensorFlow, Tableau, the integration of SQL and Tableau, the integration of SQL, Python, Tableau, Power BI, Credit Risk Modeling, and Credit Analytics

3) Entrepreneurship – Business Strategy, Management and HR Management, Marketing, Decision Making, Negotiation, and Persuasion, Tesla's Strategy and Marketing

4) Office productivity – Microsoft Excel, PowerPoint, Microsoft Word, and Microsoft Outlook

5) Blockchain for Business

All of the company’s courses are:  

Pre-scripted  

Hands-on  

Laser-focused  

Engaging  

Real-life tested  

By choosing 365 Careers, you make sure you will learn from proven experts, who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time.  

If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers’ courses are the perfect place to start. 

365 Careers Team
Creating opportunities for Business & Finance students
365 Careers Team
  • 4.5 Instructor Rating
  • 109,998 Reviews
  • 467,257 Students
  • 3 Courses

365 Careers is the #1 best-selling provider of finance courses on Udemy. The company’s courses have been taken by more than 120,000 students in 199 countries. People working at world-class firms like Apple, PayPal, and Citibank have completed 365 Careers trainings.

Currently, the firm focuses on the following topics on Udemy:

1) Finance – Finance fundamentals, Financial modeling in Excel, Valuation, Accounting, Capital budgeting, Financial statement analysis (FSA), Investment banking (IB), Leveraged buyout (LBO), Financial planning and analysis (FP&A), Corporate budgeting, and applying Python for Finance

2) Data science – Statistics, SQL, Python, Business Intelligence, R, Machine Learning, and TensorFlow

3) Entrepreneurship – Business Strategy, Management and HR Management, Marketing, Decision Making, Negotiation, and Persuasion

4) Office productivity – Microsoft Excel, PowerPoint, Microsoft Word, and Microsoft Outlook

All of the company’s courses are:

  • Pre-scripted
  • Hands-on
  • Laser-focused
  • Engaging
  • Real-life tested

By choosing 365 Careers, you make sure you will learn from proven experts, who have a passion for teaching, and can to take you from beginner to pro in the shortest possible amount of time.

If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers’ courses are the perfect place to start. 

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