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Data Analysis Foundations with Python

01Introduction to Data Analysis and Python0/5

11.1 Importance of Data Analysis 21.2 Role of Python in Data Analysis 31.3 Overview of the Data Analysis Process 5Chapter 1 Conclusion 4Practical Exercises for Chapter 1

02Getting Started with Python0/5

12.1 Installing Python 22.2 Your First Python Program 32.3 Variables and Data Types 5Chapter 2 Conclusion 4Practical Exercises for Chapter 2

03Quiz for Part I: Setting the Stage0/3

3Answer Key 1Multiple Choice Questions 2True or False Questions

04Basic Python Programming0/5

13.1 Control Structures 23.2 Functions and Modules 33.3 Python Scripting 83Chapter 3 Conclusion 109Practical Exercises Chapter 3

05Setting Up Your Data Analysis Environment0/5

14.1 Installing Anaconda 24.2 Jupyter Notebook Basics 34.3 Git for Version Control 5Chapter 4 Conclusion 4Practical Exercises Chapter 4

06Quiz for Part II: Python Basics for Data Analysis0/3

3Answer Key:1Multiple-Choice Questions 2True/False Questions

07NumPy Fundamentals0/5

15.1 Arrays and Matrices 25.2 Basic Operations 35.3 Advanced NumPy Functions 5Chapter 5 Conclusion 4Practical Exercises for Chapter 5

08Data Manipulation with Pandas0/6

16.1 DataFrames and Series 36.2 Data Wrangling 26.2 Data Wrangling 46.4 Real-World Examples: Challenges and Pitfalls in Handling Missing Data 6Chapter 6 Conclusion 5Practical Exercises Chapter 6

09Data Visualization with Matplotlib and Seaborn0/5

17.1 Basic Plotting with Matplotlib 27.2 Advanced Visualizations 37.3 Introduction to Seaborn 5Chapter 7 Conclusion 4Practical Exercises - Chapter 7

10Understanding EDA0/5

18.1 Importance of EDA 28.2 Types of Data 38.3 Descriptive Statistics 5Chapter 8 Conclusion 4Practical Exercises for Chapter 8

11Quiz for Part III: Core Libraries for Data Analysis0/4

4Answer Key 1Chapter 5: NumPy Fundamentals 2Chapter 6: Data Manipulation with Pandas 3Chapter 7: Data Visualization with Matplotlib and Seaborn

12Data Preprocessing0/5

19.1 Data Cleaning 29.2 Feature Engineering 39.3 Data Transformation 5Chapter 9 Conclusion 4Practical Exercises: Chapter 9

13Visual Exploratory Data Analysis0/5

110.1 Univariate Analysis 210.2 Bivariate Analysis 310.3 Multivariate Analysis 5Chapter 10 Conclusion 4Practical Exercises Chapter 10

14Quiz for Part IV: Exploratory Data Analysis (EDA)0/2

2Answers 1Questions

15Project 1: Analyzing Customer Reviews0/4

11.1 Data Collection 21.2: Data Cleaning 31.3: Data Visualization 41.4: Basic Sentiment Analysis

16Probability Theory0/6

111.1 Basic Concepts 211.2: Probability Distributions 311.3: Specialized Probability Distributions 411.4 Bayesian Theory 6Chapter 11 Conclusion 5Practical Exercises for Chapter 11

17Hypothesis Testing0/5

112.1 Null and Alternative Hypotheses 212.2 t-test and p-values 312.3 ANOVA (Analysis of Variance)5Chapter 12 Conclusion 4Practical Exercises Chapter 12

18Quiz for Part V: Statistical Foundations0/3

3Answers 1Chapter 11: Probability Theory 2Chapter 12: Hypothesis Testing

19Introduction to Machine Learning0/5

113.1 Types of Machine Learning 213.2 Basic Algorithms 313.3 Model Evaluation 5Chapter 13 Conclusion 4Practical Exercises Chapter 13

20Supervised Learning0/5

114.1 Linear Regression 214.2 Types of Classification Algorithms 314.3 Decision Trees 5Chapter Conclusion 4Practical Exercises Chapter 14

21Unsupervised Learning0/5

115.1 Clustering 215.2 Principal Component Analysis (PCA)315.3 Anomaly Detection 5Chapter 15 Conclusion 4Practical Exercises Chapter 15

22Quiz Part VI: Machine Learning Basics0/4

4Answer Key 1Chapter 13: Introduction to Machine Learning 2Chapter 14: Supervised Learning 3Chapter 15: Unsupervised Learning

23Project 2: Predicting House Prices0/4

2Data Collection and Preprocessing 3Feature Engineering 4Model Building and Evaluation 1Problem Statement

24Case Study 1: Sales Data Analysis0/5

116.1 Problem Definition 216.2 EDA and Visualization 316.3 Predictive Modeling 5Chapter 16 Conclusion 4Practical Exercises: Sales Data Analysis

25Case Study 2: Social Media Sentiment Analysis0/5

117.1 Data Collection 217.2 Text Preprocessing 317.3 Sentiment Analysis 5Chapter 17 Conclusion 4Practical Exercises

26Quiz Part VII: Case Studies0/3

3Answers of Quiz Part VII: Case Studies 1Chapter 16: Case Study 1 - Sales Data Analysis 2Chapter 17: Case Study 2 - Social Media Sentiment Analysis

27Project 3: Capstone Project: Building a Recommender System0/4

2Data Collection and Preprocessing 4Evaluation and Deployment 3Model Building 1Problem Statement

28Best Practices and Tips0/2

118.1 Code Organization 218.2 Documentation

Data Analysis Foundations with PythonChapter 183

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