Learn how to extract meaning from complex datasets, solve real-world problems with insights, and build a career grounded in data-led impact.
Writing code to solve problems and automate solutions is a crucial skill for anyone in IT. This module teaches Python programming and its applications in system administration, automation, and cloud computing. Learners will gain hands-on experience with Git and GitHub, troubleshooting, debugging, and best practices in software development.
Applied Learning Project - Learners will complete a capstone project where they will automate system administration tasks using Python
Prerequisites and Eligibility: This course is open to learners from all educational and professional backgrounds. No prior programming experience is required - beginners and experienced learners alike can benefit.
This module introduces learners to SQL and its applications in database management. SQL is a fundamental tool for querying, analyzing, and manipulating data in relational databases.
Applied Learning Project - Learners will design and query a relational database to solve real-world data problems.
Prerequisites and Eligibility: Basic understanding of data structures and programming concepts is helpful but not required.
This module provides hands-on experience with machine learning techniques and their applications
Applied Learning Project - Learners will develop and fine-tune an ML model using real-world data
Prerequisites and Eligibility: Python and statistics knowledge is recommended.
This module covers business intelligence and data visualization using Power BI, a leading analytics tool.
Applied Learning Project - Learners will build an interactive business intelligence dashboard using real-world datasets.
Prerequisites and Eligibility: Basic knowledge of Excel or databases is recommended.
This module focuses on big data processing and distributed computing using PySpark.
Applied Learning Project - Learners will process and analyze large datasets using PySpark.
Prerequisites and Eligibility: Familiarity with Python and SQL is recommended.
This module introduces Dataiku, a collaborative data science platform, allowing users to build machine learning models and automate workflows.
Applied Learning Project - Learners will use Dataiku to build an end-to-end machine learning pipeline.
Prerequisites and Eligibility: Basic knowledge of data analysis and Python is recommended.
This module explores the applications of Large Language Models (LLMs) in NLP and AI-driven analytics.
Applied Learning Project - Learners will fine-tune an LLM for a specific NLP task.
Prerequisites and Eligibility: Familiarity with Python and machine learning concepts is recommended.
Students will complete a real-world analytics project, using SQL and Dataiku for data collection, Python and PySpark for processing, and Power BI for visualization. They'll build predictive models, apply LLM tools for text analysis, and automate workflows. The project ends with a dashboard and presentation showcasing end-to-end analytical and business insights.
Prerequisites and Eligibility: Those completing all core modules - including Python, SQL, Dataiku, PySpark, Applied Machine Learning, Applied LLM and Power BI - will be eligible to undertake the capstone. This ensures a solid foundation for delivering a complete, end-to-end analytics solution