Free Data Science Courses on Great Learning Academy 2024 March - answersQ

Free Data Science Courses on Great Learning Academy

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Learn all the concepts involved in data science using these free data science courses provided by Great Learning.

FREE DATA SCIENCE COURSES WITH CERTIFICATE

What is Data Science?

Data Science is an inter-disciplinary field that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract knowledge and insights from many structural and unstructured data.

 

Growing demand for Data Scientists:

The need for quality professionals in data science has been tremendously rising for the past few years. Harvard Business Review deemed data scientist “The sexiest job of the 21st century”.  A report from IBM predicts that the demand for data skills will grow by 15% through 2020, and demand for data scientists and advanced analysts will grow by nearly 30%.

Here, are 16 free courses for learning Data Science with more than 20 hours of content and you can also get a free certificate after completing each of these courses from Great Learning Academy.

1. Data Science Foundations

Level: Beginner | Duration: 1.5 hours

In this course, you will learn all the fundamentals of Data Science and Data Science Life Cycle. This course will also introduce you to the analytics landscape.

2. Introduction to R

Level: Beginner | Duration: 1 hour

This course will be walking you through the basic concepts in R such as data types, data structures, control statements etc. along with the hands-on for each.

3. Basics of Exploratory data analysis

Level: Beginner | Duration: 1 hour

In this course you will learn basics of EDA, how to use them in R, Visualization using most popular R packages such as dpyr, ggplot2.

4. Probability for Data Science

Level: Beginner | Duration: 1 hour

This course will give you the basic knowledge of Probability and will make you familiar with the concept of Marginal probability and Bayes theorem.

5. Statistical Methods for Decision Making

Level: Intermediate | Duration: 2 hours

The Statistical Methods for Decision Making (SMDM) course teaches you how to use statistics to help take a real-world problem and apply various techniques to make effective business decisions.

6. Predictive Modeling and Analytics – Regression

Level: Intermediate | Duration: 2 hours

Predictive Modeling encompasses a linear techniques that can be used by organizations to predict continuous (for example, sales or demand data) as well as categorical (is someone a buyer or non-buyer?) dependent variables based on a host of input variables (independent variables).

7. Clustering in R

Level: Beginner | Duration: 3 hours

This comprehensive course on machine learning explains the overview of machine learning concepts in R. The reasons behind the concepts of machine learning, clustering concepts and applications of machine learning. The course will explain machine learning using a real world datasets to ensure that learning is practical and hands-on.

8. Data Visualization using Tableau

Level: Beginner | Duration: 1.5 hours

This course on Data Visualization With Tableau will help you understand everything you need to get started with Tableau.

9. Data Visualization With Power BI

Level: Beginner | Duration: hours

This course on Data Visualization With Power BI will help you understand everything you need to get started with Power BI.

10. Financial Risk Analytics

Level: Beginner | Duration: 1.5 hours

This course provides an introduction to Financial Risk Analytics and will help you understand how to assess credit risk, how to model credit risk and also look at methods of optimizing risk.

11. Marketing and Retail Analytics

Level: Beginner | Duration: 3 hours

This beginner course explains some basic terminologies used in marketing and discusses an application of analytics in retail. Marketing analytics is the process of measuring, managing and analyzing marketing performance to maximize effectiveness and to optimize return on investment. The course also explains RFM, a marketing technique that is used to determine quantitatively which customers are the best ones by examining factors such as recency of purchase, frequency of purchase, and how much a customer spends.

12. Marketing and Retail Analytics – Advanced

Level: Advanced | Duration: 1.5 hours

This is an advanced course that increases your knowledge in marketing especially customer segmentation. This course is a further expansion for Marketing and Retail Analytics. Marketing analytics is the process of measuring, managing and analyzing marketing performance to maximize effectiveness and to optimize return on investment. The course explains the concept of customer segmentation using Cluster Analysis.

13. Excel for Intermediate Level

Level: Intermediate | Duration: 2.5 hours

You will learn to use formulas to do complex calculations to analyse your data. You will also get an extensive understanding of concepts such as data cleaning, data visualization, Aggregation and charts.

14. Analytics on SAS

Level: Beginner | Duration: 2.5 hours

This course gives you a brief introduction to SAS. Then you’ll get hands-on experience as you go through the guide and experiment with sample SAS programs. At the end of the guide, you’ll find information about other SAS features, SAS Arrays, SAS macros and procedures, Logical and conditional statements.

15. Linear Programming for Data Science

Level: Beginner | Duration: 2.5 hours

In this course you will get introduced to Linear Programming, it’s Graphical method, sensitivity analysis, and assumptions in Linear Programming and some hand-on exercise.

16. Classification using Tree-Models

Level: Beginner | Duration: 1.5 hours

this course on tree-based classifiers will help you understand about decision trees, random forests and how to implement them in R.

Make use of these free data science courses to learn the most in-demand skill. You can also get a free certificate after completing these courses and showcase it on your profile. 

Check out other free courses on GREAT LEARNING – CLICK HERE

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