Advanced Computing Curriculum

Machine Learning Architecture

A rigorous mathematical and algorithmic exploration of statistical learning models, deep topologies, and pattern recognition frameworks.

TRACK STATUS:
Fully Verified
TOTAL CONTENT:
8 Modules / 80 Assessment Items
MODULE 01 10 MCQs

Introduction to Machine Learning

What is Machine Learning? Types of Machine Learning: Supervised, Unsupervised, Reinforcement Learning Applications of Machine Learning Overview of ML Tools and Libraries (Scikit-Learn, TensorFlow, PyTorch)
Active Module Quiz
MODULE 02 10 MCQs

Data Preprocessing & Feature Engineering

Importance of Data Cleaning Handling Missing Data and Outliers Feature Scaling and Transformation Feature Selection Techniques
Active Module Quiz
MODULE 03 10 MCQs

Supervised Learning Algorithms

Linear Regression and Logistic Regression Decision Trees and Random Forests Support Vector Machines (SVM) Model Evaluation Metrics (Accuracy, Precision, Recall, F1-score)
Active Module Quiz
MODULE 04 (EXTENSION) 10 MCQs

Naive Bayes Classification

Bayes' Theorem Foundations & Probability Spaces The Class Conditional Independence Assumption Algorithmic Structural Variations: Gaussian, Multinomial, & Bernoulli Handling Zero-Frequency Anomalies via Laplace Smoothing
New Extension Module Quiz
MODULE 05 10 MCQs

Unsupervised Learning Algorithms

Clustering Techniques (K-Means, DBSCAN, Hierarchical Clustering) Principal Component Analysis (PCA) for Dimensionality Reduction Anomaly Detection Methods
Active Module Quiz
MODULE 06 10 MCQs

Neural Networks & Deep Learning Basics

Introduction to Neural Networks Activation Functions and Backpropagation Introduction to Deep Learning and Convolutional Neural Networks (CNNs) Hands-on Implementation using TensorFlow/Keras
Active Module Quiz
MODULE 07 10 MCQs

Model Optimization & Hyperparameter Tuning

Cross-Validation Techniques Grid Search vs. Random Search Regularization Techniques (L1, L2) Bias-Variance Tradeoff
Active Module Quiz
MODULE 08 10 MCQs

Real-World Applications of Machine Learning

ML in Healthcare, Finance, and E-commerce Natural Language Processing (NLP) Basics Image and Speech Recognition Ethical Considerations and Bias in ML
Active Module Quiz