Foundational ML Course

Introduction to Machine Learning With Python For Beginners

Master the Fundamentals of Machine Learning Using Python – Crafted for Beginners and Professionals Alike.

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Course Detail

Embark on your journey into the world of Machine Learning with a course specifically designed for beginners. This comprehensive program introduces you to the fundamentals of machine learning, guiding you through the essential concepts and tools you need to start building your own models with Python. From understanding key algorithms to applying them in real-world scenarios, you’ll gain hands-on experience with the tools and techniques that power modern AI applications.

Course Features

  • Beginner-Friendly Approach: No prior AI/ML experience required.
  • Hands-On Python Coding: Gain practical experience with guided exercises and real-world projects.
  • Industry-Relevant Skills: Learn the tools and techniques that are in high demand across various industries.
  • Comprehensive Curriculum: Cover everything from the fundamentals of supervised and unsupervised learning to the intricacies of model evaluation and validation.
  • Get certified: Start building your career in AI & ML with credentials from School of Machine Learning.

Farhan Hussain

AI & ML Specialist

Farhan Hussain, an avid AI/ML enthusiast and educator, brings his passion and expertise to this course. Holding a graduate degree in Computer Science from Simon Fraser University, Canada with a specialization in machine learning, Farhan is dedicated to teaching the practical applications of AI/ML in the real world.

  • Full Lifetime Access.
  • Access on Mobile and TV.
  • Certificate of Completion.

Course Content

26 lessons • 16 coding exercises • 9 Quizzes

  • Video: What is Machine Learning
  • Video: Types of Machine Learning Part 1 (Supervised Learning)
  • Video: Types of Machine Learning Part 2 (Unsupervised Learning)
  • Video: Types of Machine Learning Part 3 (Reinforcement learning)
  • Article: Key Concepts in Machine Learning
  • Quiz: ML Intro
  • Video: Google Colab & Jupyter Notebook
  • Video: NumPy Part 1
  • Video: NumPy Part 2:
  • Quiz: Notebook & NumPy
  • Video: Pandas Part 1
  • Video: Pandas Part 2
  • Quiz: Pandas
  • Video: Matplotlib Part 1
  • Video: Matplotlib Part 2
  • Quiz: Matplotlib
  • Video: Linear Regression Part 1
  • Video: Scikit-learn
  • Video: Linear Regression Part 2
  • Article: Model Evaluation & Validation
  • Quiz: Linear Regression & Model Evaluation
  • Video: Logistic Regression Part 1
  • Video: Logistic Regression Part 2
  • Quiz: Logistic Regression
  • Video: Decision Trees Part 1
  • Video: Decision Trees Part 2
  • Quiz: Decision Trees
  • Video: Clustering with K-Means Part 1
  • Video: Clustering with K-means Part 2
  • Quiz: K-Means
  • Video: Project Part 1 (Intro)
  • Video: Project Part 2 (Dataset)
  • Video: Project Part 3 (Preprocessing & Feature Engineering)
  • Video: Project Part 4 (Applying Algorithm)
  • Video: Project Part 5 (Recommendation)
  • Video: Project Part 6 (What’s Next)
  • Quiz: Recommendation Systems
  • Certificate of Completion

FAQs

Need more info? Take a look at our FAQs.

No, the course is designed to be accessible even for those new to AI and ML.

Python programming language and a computer with internet connection.

Yes this course is focused on machine learning concepts with hands-on coding exercises.

This course should take 10-15 hours to complete. This is a self-paced learning course and it is highly encouraged to take breaks after each lesson.

Yes, upon successful completion, you will receive a certifcate from the School of Machine Learning.

Although you are required to complete all quizzes (each quiz can only be attempted once), there is no minimum percentage required to pass each quiz.

Yes, you will have a lifetime access to the course material, so you can revisit it anytime.

Absolutely! This course provides practical skills and a project portfolio that are valuable for anyone looking to start or advance their career in AI and ML.

If you have a good foundation in Python, this course will be easy. This course is built for beginner audience in mind.

Enroll Now and Start Your ML Journey!

Whether you’re new to coding or looking to expand your skill set, this course provides a solid foundation in machine learning, offering a perfect blend of theory and practical application. By the end of this course, you’ll be equipped to tackle machine learning projects with confidence and have a portfolio-ready to showcase your skills

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