Course Description
This intensive 5-day course provides a comprehensive introduction to machine learning, covering fundamental concepts, popular algorithms, and practical applications. Participants will gain hands-on experience with Python-based tools and frameworks, learning to build, evaluate, and deploy machine learning models for real-world problems.
Learning Objectives
- Understand core machine learning concepts and algorithms
- Gain proficiency in using Python for data analysis and model development
- Learn to build and evaluate supervised and unsupervised learning models
- Explore neural networks and deep learning techniques
- Develop skills to implement end-to-end machine learning projects
Course Modules
Day 1: Introduction to Machine Learning and Python
- Overview of machine learning and its applications
- Python fundamentals for data science
- Data preprocessing and exploratory data analysis
- Introduction to scikit-learn library
Day 2: Supervised Learning - Classification and Regression
- Linear and logistic regression
- Decision trees and random forests
- Support Vector Machines (SVM)
- Model evaluation and validation techniques
Day 3: Unsupervised Learning and Dimensionality Reduction
- Clustering algorithms (K-means, hierarchical clustering)
- Principal Component Analysis (PCA)
- Feature selection and engineering
- Anomaly detection techniques
Day 4: Neural Networks and Deep Learning
- Artificial Neural Networks (ANN) fundamentals
- Deep learning architectures
- Convolutional Neural Networks (CNN) for image processing
- Recurrent Neural Networks (RNN) for sequence data
Day 5: Advanced Topics and Project Implementation
- Ensemble methods and boosting algorithms
- Natural Language Processing (NLP) basics
- Introduction to reinforcement learning
- End-to-end machine learning project implementation
Practical Wins for Participants
- Build a predictive model for customer churn analysis
- Develop an image classification system using deep learning
- Create a recommendation engine using collaborative filtering
- Implement a sentiment analysis tool for social media data
Credits: 5 credit per day
Course Mode: full-time
Provider: Blackbird Training Centre
