Hands-on training focused on real-world data analysis, business problem solving, and industry-relevant tools to build job-ready analytics skills.
This program is designed to build strong analytical thinking and practical data skills. Learners work on real-world business problems using industry-relevant tools and projects, enabling them to make data-driven decisions and become job-ready.
Introduction to data science, analytics, machine learning, and AI with real industry use cases and business problem framing.
Python environment setup and core programming concepts including variables, data types, and operators.
Develop computational thinking using flowcharts, pseudo-code, and logic-based programs.
Understanding KPIs, performance metrics, and analytics-driven decision frameworks.
Essential math concepts such as averages, ratios, trends, and growth with business examples.
Database fundamentals and SQL queries to extract, filter, and analyze structured data.
Conditions, loops, functions, debugging techniques, and writing reusable Python code.
Data cleaning, transformation, and exploratory analysis using Pandas.
Statistics concepts, distributions, probability, and A/B testing for data insights.
Handling missing data, feature creation, and data visualisation for insight storytelling.
Introduction to regression and classification models with evaluation techniques.
End-to-end capstone project with resume building, GitHub portfolio, and interview preparation.
