Introduction to Data Analytics Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This beginner-friendly course by IBM introduces the fundamentals of data analytics in under four weeks. Designed for those new to the field, it covers the data analysis lifecycle, key tools like Excel, R, and Python, and real-world applications across industries. Each module blends conceptual learning with hands-on discussions and walkthroughs, offering a clear path to understanding data roles, ecosystems, and visualization techniques. Total time commitment: approximately 16-20 hours.
Module 1: Introduction to Data Analytics
Estimated time: 4 hours
- Role of data analysts in business
- Understanding the data ecosystem
- Principles of data-driven decision-making
- Real-world case discussions on data use
Module 2: Analytical Skills and Tools
Estimated time: 4 hours
- Basic concepts of spreadsheets and their role in analysis
- Introduction to SQL for data querying
- Overview of R for statistical computing
- Introduction to Python for data tasks
Module 3: Data Ecosystem and Key Concepts
Estimated time: 4 hours
- Understanding databases and their structures
- Introduction to data warehouses
- Exploring data lakes and their uses
- Simple walkthroughs of data environments
Module 4: Data Visualization and Insights
Estimated time: 4 hours
- Principles of effective data visualization
- Using charts and graphs to convey meaning
- Building dashboards for insight delivery
- Storytelling with data
Prerequisites
- Familiarity with basic computer operations
- No prior coding experience required
- Basic understanding of business concepts helpful
What You'll Be Able to Do After
- Explain the data analysis lifecycle and its applications
- Identify key roles and structures in the data ecosystem
- Compare and contrast core data analytics tools
- Create basic visualizations to communicate insights
- Apply foundational concepts to real-world data scenarios