- Lectures: 28
- Students: 1
- Duration: 72 hours
WHAT YOU WILL LEARN (TERM 1)
Data Analysis in Excel
Statistics for Analytics
Programming in R
Intro to Machine Learning
ENTRY PROFILE
Undergraduates , Graduates
Working Professionals
Anyone who wishes to be a Data Analyst and has basic knowledge on Microsoft Office Tools
EXIT PROFILE & JOB OPPORTUNITIES
Data Analysts
Research Associates
Business Analysts
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Overview
In this section we'll show you how this course has been structured and how to get the most out of it. We'll also show you how to solve the exercises and submit quizzes.
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Basics
In this section you'll learn some basic concepts of programming languages and how to use them. You'll also learn how to write clean code using different code editors and tools.
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Advanced
In this section you'll learn some core concepts of Object Oriented Programming. You'll also learn how to structure the data, debug and handling exceptions.
- Introduction to Statistics and Analytics
- Data Representation
- Forecasting Techniques
- Causality and Correlation
- Hypothesis Testing
- Parametric and Non-Parametric Tests
- Programming in R
- Overview of R and R Studio
- Introduction to R libraries
- Data structures and data types in R
- Variables and Operators
- Functions in R
- Statements in R
- Machine Learning
- Introducing Machine Learning
- Managing and Understanding Data
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Conclusion
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