Build Machine Learning Models Faster with the Power of Generative AI.
Master Machine Learning with Generative AI and Python.
Accelerate every stage of the machine learning lifecycle using Generative AI. Learn how to build, optimize, fine-tune, and automate predictive models with Python while leveraging AI assistants such as ChatGPT, Gemini, Claude, DeepSeek, and Copilot to improve productivity and model performance.
2-Day Training
HRDC Claimable
IS YOUR TEAM FACING THESE CHALLENGES?
Building ML models takes too long.
Data preprocessing, coding, debugging, and model optimization consume significant development time before meaningful insights can be delivered.
Model accuracy is difficult to improve.
Selecting the right algorithms, tuning hyperparameters, and optimizing performance often require extensive experimentation and expertise.
Repetitive coding slows productivity.
Machine learning engineers repeatedly write similar preprocessing, feature engineering, and model evaluation code across different projects.
AI tools are underutilized.
Many professionals have access to ChatGPT, Copilot, Gemini, and other AI assistants but struggle to use them effectively for machine learning development.
ML workflows remain largely manual.
From data preparation to deployment, repetitive tasks reduce efficiency and increase the likelihood of errors.
AI is evolving faster than technical skills.
Organizations need professionals who can combine Python, machine learning, and Generative AI to stay competitive in an increasingly AI-driven world.
Mastering Machine Learning with Generative AI
FULL
Normal price: RM 2,500
2-day Instructor-led training
Hands-on practical sessions
HRDC claimable
Only 22 seats are available
First come, first served
Registration closes on 7th August 2026
Date: 13 - 14 August
Mode: Physical (GemRain Premises)
Bring your own laptop
WHAT YOU WILL LEARN
✅
Build Machine Learning Models with AI
Learn how Generative AI assists with model selection, Python code generation, predictive analytics, and machine learning development using industry-standard libraries.
✅
Optimize Models with AI Assistance
Discover how AI accelerates feature engineering, hyperparameter tuning, debugging, and model optimization to improve prediction accuracy and reduce development time.
✅
Automate Machine Learning Workflows
Leverage AI-powered tools to automate data preprocessing, model evaluation, workflow generation, and end-to-end machine learning pipelines.
✅
Apply AI to Real-World Projects
Build practical predictive models using Python, Scikit-learn, Jupyter Notebook, and modern Generative AI assistants through guided hands-on exercises.
AFTER ATTENDING THIS TRAINING, PARTICIPANTS WILL BE ABLE TO
Build predictive machine learning models using Python and Generative AI.
Automate data preprocessing and feature engineering tasks.
Improve model accuracy through AI-assisted optimization techniques.
Generate, debug, and refine Python code using modern AI assistants.
Automate end-to-end machine learning workflows.
Apply AI-powered techniques to solve real-world business problems.
BEFORE vs AFTER
BEFORE | AFTER | |
Manual ML development | ➡️ | AI-assisted model development |
Time-consuming coding | ➡️ | Faster AI-generated Python code |
Trial-and-error optimization | ➡️ | Intelligent hyperparameter tuning |
Manual preprocessing | ➡️ | Automated data preparation |
Isolated ML workflows | ➡️ | End-to-end AI automation |
Basic predictive models | ➡️ | Optimized production-ready models |