Big Data Computation and Forecasting

Course practice (1 hour per session)

The course is offered as a short eight-session course. Each session (3.5 hours) includes a dedicated one-hour course practice where you will apply the concepts covered in class. This is a guided, interactive session where you can experiment with real-world data, practice coding and algorithms, and clarify any doubts. There’s no pressure—this is a learning opportunity designed to help you build confidence with Big Data tools and forecasting techniques.

Individual assignments

You will complete two individual assignments in total base on your course practice, each carefully designed to reinforce your learning in manageable steps:

• Assignment 1: Focuses on understanding and handling large datasets, performing basic data transformations, and running simple analytics.
• Assignment 2: Introduces forecasting techniques where you will apply statistical and machine learning models to make predictions based on data trends.

Each assignment is structured with clear instructions, sample code, and support, so you never feel lost. They are designed to be achievable even if you are new to Big Data.

Final assignment

The final assignment brings everything together. You will work on a small project where you use real-world datasets to perform forecasting at scale. You will have plenty of time to complete it (usual up to 4 weeks), and support will be available to guide you. The focus is on applying what you’ve learned in a meaningful way rather than just testing your skills.