Course Overview
Start your journey into Artificial Intelligence and Machine Learning with practical training designed to build strong foundations in Python, data handling and machine learning concepts. The AI & Machine Learning Starter Program introduces learners to Artificial Intelligence and Machine Learning, including their use cases and industry applications. Students learn Python for AI and Data Handling, including Python basics, NumPy and Pandas. The program also covers the essential Mathematics Foundations for Machine Learning, including statistics, probability and basic linear algebra concepts. The course introduces Data Preprocessing and Exploratory Data Analysis (EDA), including data cleaning and feature engineering. Learners then progress to Supervised Learning Algorithms, covering regression and classification techniques such as Decision Trees and SVM. The program also introduces Unsupervised Learning, including clustering and PCA, followed by Model Evaluation and Improvement, covering evaluation metrics and cross-validation. Students complete a basic end-to-end Machine Learning project / capstone, helping them apply the concepts learned throughout the program. The course also provides an introduction to Neural Networks and Deep Learning fundamentals.
Syllabus & Modules
- What is Artificial Intelligence
- What is Machine Learning
- AI and ML Use Cases
- Industry Applications of AI & Machine Learning
- Python Basics
- Python for AI
- NumPy
- Pandas
- Data Handling with Python
- Statistics
- Probability
- Linear Algebra Essentials
- Mathematical Foundations for Machine Learning
- Data Preprocessing
- Data Cleaning
- Exploratory Data Analysis (EDA)
- Feature Engineering
- Introduction to Supervised Learning
- Regression
- Classification
- Decision Trees
- Support Vector Machines (SVM)
- Introduction to Unsupervised Learning
- Clustering
- Principal Component Analysis (PCA)
- Model Evaluation
- Evaluation Metrics
- Cross Validation
- Model Improvement
- End-to-End Machine Learning Project
- Data Preparation
- Model Development
- Model Evaluation
- Project Implementation
- Introduction to Neural Networks
- Deep Learning Basics
- Basic Neural Network Concepts
- Introduction to Deep Learning Applications
Eligibility Criteria
Career Opportunities
Junior Machine Learning Trainee
Assist with basic machine learning workflows, data preparation and model evaluation.
AI / ML Intern
Work on practical AI and machine learning projects under supervision.
Junior Data Analyst
Work with Python, Pandas and data preprocessing to analyze datasets and prepare insights.
Python Data Analyst
Use Python, NumPy and Pandas for data handling, cleaning and analysis.
Software & Tools Covered
Ready to enroll in AI & Machine Learning Starter Program?
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