12-Week Machine Learning For Beginners

Learn ML in just 1 hour a day! This flexible, self-paced course is 100% online.

Master the fundamentals of machine learning in 12 weeks with our hands-on, beginner-friendly course. Over 60 hours, you’ll learn key algorithms, data processing, and model-building using Python and tools like Scikit-learn. Plus, you’ll have a dedicated ML tutor to support you every step of the way. By the end, you’ll be ready to build real-world ML solutions and advance your tech career.

What I will learn?

By the end of this course, you will be able to:
Build and deploy machine learning models in real-world environments.
Use Python libraries to create ML solutions.
Implement data preprocessing, feature engineering, and model evaluation techniques.
Apply ethical considerations to ensure responsible and fair use of AI.

Optimize ML models for performance and scalability in diverse applications.
Work with supervised and unsupervised learning techniques.
Develop a professional portfolio of ML projects to showcase your expertise.
Transition into a machine learning role, equipped with the skills to solve industry challenges.

About Course

This 12-week course is tailored for beginners eager to launch a career in machine learning. You’ll gain essential skills through a dynamic blend of interactive lessons, hands-on coding exercises, and real-world projects.

Focusing on practical applications, this course ensures you can confidently build and deploy machine learning models using Python. Beyond just theory, you’ll apply what you learn to solve real-world challenges. With expert guidance and personalized support, you’ll establish a solid foundation in machine learning, positioning you to advance in the tech industry with confidence.

12-Week Machine Learning Course Curriculum

Introduction To Machine Learning

Introduction to Python For Machine Learning

Introduction to NumPy, Pandas, Scikit Learn and Matplotlib

Essential Statistics For Machine Learning

Introduction to Probability For Machine Learning

Fundamental Supervised Machine Learning Techniques

Advanced Supervised Machine Learning Techniques

Fundamental Unsupervised Machine Learning Techniques

Advanced Unsupervised Machine Learning Techniques

Cross Validation and Hyperparameter Tuning

Build Your Machine Learning Portfolio

Requirements

No prior experience in machine learning is required, but a willingness to engage with technical content is essential.
Basic Math Understanding: Comfort with high school-level statistics and probability.
Problem-Solving Skills: A logical approach to solving complex problems.
Curiosity and Motivation: A strong desire to learn and apply machine learning in real-world scenarios.

Material Includes

Pre-Course Skills Level Assessment.
Interactive Lessons & Coding Exercises.
Real-World Projects & Python Notebooks.
Quizzes: Regular tests to gauge your understanding and progress.
Networking & Career Coaching.

€ 1500

Get in touch to find out financing options.

Enroll Now

Includes:

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