Limitless Learning

1. Introduction to Data Analysis

   - The role of a data analyst

   - Data analysis process overview

   - Types of data and data sources

2. Statistics Fundamentals

   - Descriptive statistics

   - Probability basics

   - Inferential statistics

   - Hypothesis testing

3. Data Collection and Cleaning

   - Data collection methods

   - Data quality assessment

   - Data cleaning techniques

   - Handling missing data

4. Data Visualization

   - Principles of data visualization

   - Chart types and their uses

   - Tools: Tableau, Power BI

5. Spreadsheet Skills (Excel)

   - Advanced functions and formulas

   - Pivot tables and charts

   - Data modeling in spreadsheets

6. Databases and SQL

   - Database basics

   - SQL queries for data extraction

   - Joins and subqueries

7. Programming for Data Analysis

   - Python basics

   - Data manipulation with pandas

   - Creating scripts for data analysis

8. Exploratory Data Analysis (EDA)

   - Techniques for exploring datasets

   - Pattern recognition

   - Outlier detection

9. Advanced Analytics Techniques

   - Regression analysis

   - Cluster analysis

   - Time series analysis

10. Big Data Fundamentals

    - Introduction to big data concepts

    - Overview of big data technologies (e.g., Hadoop, Spark)

11. Data Ethics and Privacy

    - Ethical considerations in data analysis

    - Data privacy regulations (e.g., GDPR, CCPA)

12. Project Work and Case Studies

    - Applying learned skills to real-world datasets

    - Developing a portfolio project

13. Business Intelligence and Reporting

    - Creating dashboards

    - Report writing and presentation skills

14. AI & Machine Learning Basics

    - Introduction to machine learning concepts

    - Simple classification and regression models