IBM Generative AI Engineering Professional Certificate
IBM's 16-course professional certificate on Coursera — LLMs, transformers, fine-tuning, RAG and LangChain. Completed October 2026.
- Issuer: IBM, via Coursera
- Completed: 17 October 2026
- Courses: 16 (15 with individually verifiable Credly badges)
- Verify: coursera.org/account/accomplishments/specialization/DT7I0XVP5JQZ
What it covers
A full path from AI fundamentals to building and adapting generative AI systems: Python for data and machine learning, Deep Learning, NLP, the Transformers architecture, LLM data preparation, Fine-Tuning (instruction tuning and DPO), Prompt Engineering, and RAG (Retrieval-Augmented Generation) applications and agents with LangChain — hands-on with PyTorch and Hugging Face.
It complements my agent-runtime work in Akashi and my local-rag-chatbot by grounding the application layer in how the models are built and trained.
Courses
- Generative AI Essentials · Artificial Intelligence Essentials V2 · Generative AI: Prompt Engineering
- Building Generative AI-Powered Applications with Python · Python Project for AI and Application Development
- Data Analysis with Python · Machine Learning with Python (V2) · Deep Learning Essentials with Keras
- Generative AI and LLMs: Architecture and Data Preparation · Generative AI Foundational Models for NLP & Language Understanding · Generative AI Language Modeling with Transformers
- Generative AI Engineering with Transformers & LLMs · Generative AI Advanced Fine-Tuning for LLMs
- Generative AI Applications Specialist · AI Agents Using RAG and LangChain
Why it matters
Most of my daily work is at the application layer. This program fills in the layer beneath — how models are trained, adapted and evaluated — which informs choices such as when to use RAG (Retrieval-Augmented Generation) versus fine-tuning, and it gave me the foundations I then applied hands-on in Real-time Data Systems, fine-tuning a time-series foundation model with PyTorch.