ITonlinelearning Academy

1.1 Introduction Part 1

1.2 Introduction Part 2

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2.1 What is Data Analysis?

2.2 The Data Analysis Process

2.3 The Data Analysis Process

2.4 Ask the Right Questions!

2.5 Collect the Data

2.6 Cleaning the Data

2.7 Analysing the Data

2.8 Interpret the Data

2.9 Communicate Your Insights

2.10 Communicate

2.11 Module Summary

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3.1 Where Do We Use Data Analysis?

3.2 The Data Set of Skills Needed for Data Analysis

3.3 Common Data Analysis Tools

3.4 Why Program Data?

3.5 The Future of Data Analysis

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4.1 Understanding Data Sources

4.2 File Based Data Sources

4.3 Databases

4.4 APIs

4.5 Manual Data Entry

4.6 Streaming Data Sources

4.7 Practical Considerations

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5.1 Understanding Categorical & Numerical Data Types

5.2 Types of Numerical Data

5.3 Categorical Data

5.4 Key Differences

5.5 Working With Data Types

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6.1.1 Understanding Explanatory Data Analysis (EDA)

6.1.2 What is Exploratory Data Analysis?

6.1.3 Why is EDA Important?

6.1.4 Key Steps in EDA

6.1.5 Common EDA Techniques

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