Data Analytics

Curriculum

1. Week 1

   Introduction to Analytics

   Understand Data Analytics, analytics fundamentals, business-driven analytics and using data to solve real-world problems.

2. Statistical Foundations

   Statistical concepts, understanding data patterns and applying statistical analysis to support better decisions.

3. Data Collection and Management

   Collecting data, managing datasets and organizing data effectively for analysis.

4. Week 2

   Data Cleaning and Preprocessing

   Cleaning raw data, preparing datasets, handling data quality issues and making data analysis-ready.

5. Exploratory Data Analysis (EDA)

   Exploring datasets, identifying patterns and trends, discovering insights and understanding relationships in data.

6. Predictive Analytics and Modeling

   Analyzing historical data, building predictive models, forecasting future outcomes and supporting data-driven decisions.

7. Week 3

   Prescriptive Analytics and Optimization

   Moving from prediction to action, finding better business decisions and optimizing business outcomes.

8. Data Visualization and Storytelling

   Creating dashboards, visualizing data, presenting insights clearly and turning complex data into understandable stories.

9. Programming and Analytics Tools

   Excel, SQL and Power BI for analyzing datasets, building dashboards and working effectively with analytics tools.

10. Week 4

    Big Data and Cloud Analytics

    Understanding large-scale data, big-data analytics and cloud-based analytics concepts.

11. Domain-Specific Applications

    Applying analytics to finance, operations, marketing and product teams while solving business problems using data.

12. Ethics, Data Governance and Security

    Responsible data usage, data governance, data security and protecting and managing business data.

13. Real-World Case Studies and Projects

    Applying analytics to real business scenarios, working with real datasets, building practical solutions and developing industry-ready problem-solving skills.

What you walk away with

• A portfolio of practical analytics projects using real-world datasets, dashboards and business case studies
• Hands-on experience with Excel, SQL, Power BI, statistics, data visualization and predictive analytics
• Industry-ready data storytelling, problem-solving and business analytics skills for finance, operations, marketing and product teams