Data Science & Generative AI Certificate – IBM & TimesPro

The curriculum of the IBM & TimesPro Advanced Certificate in Data Science and Generative AI is structured into eight learning paths that collectively span foundational to advanced concepts across the data science and AI landscape. The programme begins with IBM's Foundation of Data Science modules, establishing core programming, data wrangling, and analytical thinking skills using Python. This is followed by EDA and Statistics from IBM, which builds rigorous quantitative and exploratory analytical capabilities. TimesPro's SQL and Database Analytics module develops learners' ability to query, manage, and derive insights from relational databases. The Machine Learning and Deep Learning paths from TimesPro cover both classical and neural network-based modelling techniques with practical implementation emphasis. IBM's Generative AI in Data Science module introduces large language models, retrieval-augmented generation, prompt engineering, and GenAI-powered application development. Responsible AI from IBM addresses ethical frameworks, data privacy regulations, and principles for trustworthy AI deployment. The programme culminates in a TimesPro-led Capstone Project where learners build end-to-end data science and GenAI solutions, supported by assignments, case studies, and career services.

The programme's eight learning paths are carefully sequenced to build expertise progressively across the data science and generative AI stack. The Foundation of Data Science path from IBM establishes core competencies in Python programming, data manipulation, and the fundamental concepts underpinning modern data workflows. The EDA and Statistics path deepens learners' ability to explore datasets, identify patterns, and apply statistical methods to draw valid analytical conclusions. SQL and Database Analytics, developed by TimesPro, trains learners to interact with relational databases, construct complex queries, and extract actionable insights from structured data. The Machine Learning path from TimesPro covers supervised and unsupervised learning algorithms, model evaluation, feature engineering, and real-world predictive modelling techniques. The Deep Learning path introduces neural network architectures, including CNNs and RNNs, with practical implementation using TensorFlow and related frameworks. IBM's Generative AI in Data Science path covers the landscape of large language models, retrieval-augmented generation, prompt engineering strategies, and the development of GenAI-powered applications relevant to enterprise contexts. IBM's Responsible AI module provides grounding in ethical AI principles, fairness, transparency, data privacy regulations, and frameworks for deploying AI responsibly in organisational settings. The programme concludes with a Capstone Project, guided by TimesPro, in which learners apply their cumulative knowledge to design and build end-to-end data science and GenAI solutions, supported by assignments, case studies, and career coaching services.