Topics

CERTIFICATE COURSE IN AI (Artificial Intelligence)-ML (Machine Learning)

STAGE 1

Python Prerequisites

Goal: Gain basic programming skills in Python.

Topics:

• Variables, data types, operators
• Conditional statements, loops
• Functions and scope
• Lists, dictionaries, sets, tuples
• File handling
• Exception handling
• Basic OOP (Classes and Objects)

STAGE 2

Data Science & Preprocessing

Goal: Learn data handling, cleaning, and exploration.

Topics:

• Pandas and NumPy for data wrangling
• Data Visualization (Matplotlib, Seaborn)
• Data Cleaning & Missing Value Treatment
• Feature Scaling, Encoding, Normalization

STAGE 3

Machine Learning with Python

Goal: Understand core ML algorithms and implement them.

Topics:

• Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, KNN
• Unsupervised Learning: K-Means, PCA, Clustering
• Model Evaluation Metrics, Cross-Validation, Grid Search
• Overfitting and Underfitting

Tools:

• Scikit-learn
• MLflow (Optional)
• Jupyter Notebook

STAGE 4

Deep Learning & AI

Goal: Dive into neural networks and build AI applications.

Topics:

• Perceptron and Activation Functions
• Forward and Backward Propagation
• Neural Networks using TensorFlow / Keras
• CNNs for Image Processing
• RNNs and LSTMs for Time Series / NLP
• Transfer Learning and Introduction to Transformers

Tools:

• TensorFlow
• Keras
• PyTorch
• OpenCV
• Hugging Face