Name: Machine Learning for Beginners
Availability: InStock

What You'll Learn

Understand what Machine Learning is and how it differs from traditional programming.
Explain supervised, unsupervised, and reinforcement learning in simple terms.
Implement basic ML models in Python (Linear Regression, Classification).
Work with datasets using Pandas and visualize results with Matplotlib.

Requirements

This course is designed for absolute beginners — no prior experience in machine learning is required.
Basic computer literacy: ability to use a web browser, download files, and open documents
Some familiarity with ICT concepts or programming logic (optional but helpful).
Access to the internet and a Google account (for running hands-on exercises in Google Colab — no installation needed).
A laptop or desktop computer with a modern web browser (Chrome, Edge, or Firefox).
While basic coding experience is an added advantage : all examples are explained step-by-step using clear Python code and datasets provided in the course resources.

This course is designed for ICT professionals, developers, and beginners who want to enter the exciting world of machine learning but don’t know where to start.
Have a background or interest in information and communication technology (ICT) and want to build coding skills in machine learning.
Are software developers, data enthusiasts, or analysts looking to understand how AI and ML are applied in real-world systems.
Are students, interns, or early-career professionals seeking practical skills that will make them more competitive in today’s data-driven job market.
Want to learn step-by-step, hands-on using simple datasets, real examples, and free tools like Google Colab — without complex math or setup requirements.
By the end of this course, learners will have a solid understanding of core ML concepts and the ability to build and test basic models in Python, opening doors to careers in data science, AI development, and automation.

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1,904 Students

2 Courses

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