SFIA AI Engineer: IBM AI Engineering Professional Certificate
Completed by Zandre Coetzee on August 19, 2025
Verified learner ·
Badge ID: V3eqE0a6R7i3qhNGune4NQ
About this Badge
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Learning objectives
- Design, implement, and evaluate deep learning models using Keras and PyTorch, including convolutional and recurrent neural networks.
- Apply advanced fine-tuning techniques to optimize large language models (LLMs) for specific NLP tasks using frameworks like Hugging Face and PyTorch.
- Develop generative AI applications using retrieval-augmented generation (RAG) and LangChain, integrating document retrieval and interactive model responses.
- Build and train transformer-based models for NLP applications, mastering concepts like attention mechanisms, positional encoding, and encoder-decoder architectures.
Skills learned
- Artificial Intelligence and Machine Learning (AI/ML)
- Machine Learning Algorithms
- Generative AI Agents
- Applied Machine Learning
- Artificial Neural Networks
- Time Series Analysis and Forecasting
- Large Language Modeling
- Natural Language Processing
- Verification And Validation
- Dimensionality Reduction
- Statistical Methods
- Text Mining
- Artificial Intelligence
- Scientific Visualization
- User Feedback
- Computer Vision
- Predictive Modeling
- Performance Tuning
- Quality Assessment
- Reinforcement Learning
- Semantic Web
- Python Programming
- Image Analysis
- Deep Learning
- Unsupervised Learning
- Feature Engineering
- Machine Learning
- Data Manipulation
- Training and Development
- ChatGPT
- OpenAI
- Tensorflow
- Network Architecture
- Data Processing
- Data Ethics
- Data Pipelines
- Statistical Analysis
- Databases
- Scikit Learn (Machine Learning Library)
- PyTorch (Machine Learning Library)
- Classification And Regression Tree (CART)
- Keras (Neural Network Library)
- User Interface (UI)
- Probability & Statistics
- Skills section collapsed. Showing 5 of 44 skills.
Learning content completed
Some of the content and skills presented have been contributed by the content provider.