Artificial Intelligence, Data Science & Machine Learning with Python
A 5-day instructor-led course designed to equip participants with practical skills in Artificial Intelligence, Machine Learning, and Data Science using Python. Learn regression, classification, clustering, time-series forecasting, and neural networks — the key engines of Industry 4.0 innovation.
Duration:
Fees with SST:
5 Days
RM 7,020.00
As organizations move into Industry 4.0, the ability to leverage Artificial Intelligence and Machine Learning is a defining skill for professionals across sectors.
This comprehensive 5-day course by GemRain Consulting builds a solid foundation in Python-based AI and ML, combining theory with real-world implementation.
Participants learn to preprocess data, build predictive models, visualize insights, and deploy solutions using libraries such as NumPy, Pandas, Seaborn, Matplotlib, and TensorFlow.
By the end of the program, participants will have implemented multiple supervised and unsupervised models, explored NLP and neural networks, and completed a capstone ML use case — gaining a complete, job-ready skillset for data-driven innovation.
Module 1: AI Foundations & Data Handling
Introduction to AI, ML, and deep learning concepts
Supervised vs. Unsupervised learning
Python setup (Anaconda, Jupyter Notebooks)
Data import/export and NumPy, Pandas basics
Module 2: Data Cleaning & Visualization
Data manipulation and normalization techniques
Handling missing data and data formatting
Exploratory Data Analysis (EDA)
Visual analytics with Matplotlib, Seaborn, and Plotly
Module 3: Supervised Learning
Linear & Logistic Regression
Time Series Forecasting (ARIMA, smoothing)
Decision Trees and Ensemble Learning (Bagging, Boosting, Random Forest, XGBoost)
Model validation and performance metrics
Module 4: Advanced ML & Unsupervised Techniques
Naive Bayes and Support Vector Machines (SVM)
Dimensionality reduction (PCA, kernel learning)
Clustering and segmentation (K-Means, Hierarchical)
Module 5: Deep Learning & NLP
Natural Language Processing (tokenization, lemmatization, WordCloud)
Artificial Neural Networks with TensorFlow
Hyperparameter tuning and validation
Capstone: End-to-end ML implementation and presentation
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Frequently Asked Questions (FAQs)
Do I need strong math skills?
Basic statistics knowledge is helpful but not mandatory — the course explains all core concepts clearly.
Will I build actual models?
Yes. You’ll train and validate multiple AI/ML models using real datasets.
Is this course theoretical or practical?
It’s 70% hands-on labs and 30% conceptual grounding.
Does it cover deep learning and NLP?
Yes. Dedicated modules focus on TensorFlow and text analytics.
Can I apply these skills at work?
Absolutely. Each module links directly to business and industry use cases.