Course Overview
Our AI & Machine Learning course is designed to provide you with a comprehensive understanding of artificial intelligence and machine learning concepts, tools, and applications. From foundational algorithms to advanced deep learning techniques, this course prepares you for a career in one of the most in-demand fields in technology.
What You'll Learn
Module 1: Introduction to AI & ML
- Understanding Artificial Intelligence concepts
- Machine Learning fundamentals
- Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
- AI vs ML vs Deep Learning
Module 2: Python for Data Science
- Python programming basics
- NumPy and Pandas for data manipulation
- Data visualization with Matplotlib and Seaborn
- Jupyter Notebooks environment
Module 3: Statistics & Mathematics
- Probability distributions
- Statistical inference
- Linear algebra fundamentals
- Calculus for machine learning
Module 4: Supervised Learning
- Linear Regression
- Logistic Regression
- Decision Trees and Random Forests
- Support Vector Machines
- Model evaluation metrics
Module 5: Unsupervised Learning
- K-Means Clustering
- Hierarchical Clustering
- Principal Component Analysis (PCA)
- Association Rule Mining
Module 6: Deep Learning
- Neural Networks fundamentals
- Convolutional Neural Networks (CNN)
- Recurrent Neural Networks (RNN)
- TensorFlow and Keras frameworks
Module 7: Natural Language Processing
- Text preprocessing techniques
- Sentiment analysis
- Named Entity Recognition
- Language models and transformers
Module 8: Computer Vision
- Image processing fundamentals
- Object detection and recognition
- OpenCV library
- Real-world computer vision applications
Module 9: Model Deployment
- Model serialization and deployment
- Flask and FastAPI for ML APIs
- Docker containerization
- Cloud deployment (AWS, GCP, Azure)
Module 10: Capstone Project
- Real-world problem solving
- End-to-end ML project development
- Portfolio building
- Industry best practices
Course Features
Duration
6 months (Part-time) / 3 months (Full-time)
Class Size
Maximum 25 students per batch
Certification
Industry-recognized certificate upon completion
Mode
Online/Offline with live instructor sessions
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