Machine Learning Fundamentals

Eligibility and Prerequisites

This course is suitable for individuals with basic programming knowledge, particularly in Python, and a fundamental understanding of mathematics, such as algebra and probability. If you are new to programming or data science, we offer preparatory materials that can help you get up to speed before starting the course.

Course Overview & Syllabus

Our Machine Learning Fundamentals course provides a comprehensive introduction to the core principles of machine learning. Throughout the course, you will gain hands-on experience with essential ML concepts and tools, you will learn:

• Introduction to Machine Learning
• Programming in Python – numpy, pandas, matplotlib
• Supervised learning – KNN, Naïve Bayes, Decision Tree, SVM, ensemble methods, linear regression, logistic regression
• Unsupervised – K-Means, hierarchical clustering, dimensionality reduction methods e.g. PCA, t-SNE
• Model training, testing, performance evaluation
• Feature Engineering
• Neural Networks
• Capstone Project

Career Opportunities after the Course

Machine Learning Engineer:

• Develop and implement machine learning models.
• Fine-tune models for optimal performance.
• Collaborate with data scientists and software engineers to build AI-powered solutions.

Data Scientist:

• Collect, clean, and analyze large datasets.
• Extract meaningful insights from data.
• Use machine learning techniques to build predictive models.

AI Research Scientist:

• Conduct research to advance the field of machine learning.
• Develop new algorithms and techniques.
• Publish research papers and present findings at conferences.

Machine Learning Consultant:

• Advise organizations on how to leverage machine learning.
• Implement machine learning solutions for clients.
• Provide technical expertise and guidance.

Other Related Roles:

• Data Engineer: Prepare and manage large datasets for analysis.
• Software Engineer: Develop software applications that incorporate machine learning components.

Product Manager: Oversee the development and launch of AI-powered products.