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Machine Learning

Machine Learning with Python: A Complete Beginner's Path

Learn machine learning from scratch with Python, covering core concepts, popular algorithms, and hands-on projects.

Learn from: the original creator. Original content published on YouTube. DigitalSkillX organizes these public resources into a structured learning path. DigitalSkillX does not claim ownership or partnership.

Lessons
24
Time
About 91 hr 33 min
Level
beginner

Now playing: Machine Learning | What Is Machine Learning? | Introduction To Machine Learning | 2026 | Simplilearn

About this path

This learning path is built from a Simplilearn YouTube playlist designed for beginners. It starts with Python basics and essential libraries, then moves into core machine learning concepts and algorithms like linear regression, decision trees, and neural networks. You'll also find practical tutorials, career guidance, and full-length courses to deepen your understanding. Each video builds on the previous one, so follow the order for a smooth learning experience.

What you will learn

  • Understand what machine learning is and its real-world applications
  • Learn Python basics and key libraries like Pandas, NumPy, and Matplotlib
  • Differentiate between supervised, unsupervised, and reinforcement learning
  • Implement and evaluate popular ML algorithms in Python
  • Gain career insights and prepare for machine learning interviews

Who this is for

Beginners who want a structured free introduction before deeper practice.

Curriculum

Section 1: Getting Started with Machine Learning

  1. Lesson 1: Machine Learning | What Is Machine Learning? | Introduction To Machine Learning | 2026 | Simplilearn

    This video introduces machine learning, explaining what it is and why it matters. It covers basic concepts and sets the stage for the rest of the playlist.

    Open on YouTube
  2. Lesson 2: Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algorithms | Simplilearn

    A broad tutorial covering machine learning basics and common algorithms. It gives an overview of how different algorithms work and where they are used.

    Open on YouTube
  3. Lesson 3: Top 10 Applications of Machine Learning | Machine Learning Applications & Examples | Simplilearn

    This video lists top applications of machine learning, from recommendation systems to healthcare. It helps you see real-world uses of the concepts you'll learn.

    Open on YouTube
  4. Lesson 4: Supervised Learning | Unsupervised Learning | Machine Learning Tutorial | 2026 | Simplilearn

    Explains supervised and unsupervised learning with examples. It clarifies the difference between the two main types of machine learning.

    Open on YouTube
  5. Lesson 5: Supervised vs Unsupervised vs Reinforcement Learning | Machine Learning Tutorial | Simplilearn

    A short comparison of supervised, unsupervised, and reinforcement learning. It helps solidify the distinctions between these three paradigms.

    Open on YouTube

Section 2: Core Algorithms and Implementation

  1. Lesson 6: Linear Regression Analysis | Linear Regression in Python | Machine Learning Algorithms | Simplilearn

    This tutorial covers linear regression, a fundamental algorithm for predicting continuous values. It includes implementation in Python.

    Open on YouTube
  2. Lesson 7: Logistic Regression | Logistic Regression in Python | Machine Learning Algorithms | Simplilearn

    Logistic regression is explained for classification problems. The video walks through the theory and Python implementation.

    Open on YouTube
  3. Lesson 8: Decision Tree In Machine Learning | Decision Tree Algorithm In Python |Machine Learning |Simplilearn

    Decision trees are introduced as a simple yet powerful algorithm. The video covers how they work and how to build one in Python.

    Open on YouTube
  4. Lesson 9: Random Forest Algorithm - Random Forest Explained | Random Forest in Machine Learning | Simplilearn

    Random forest, an ensemble method, is explained in detail. It shows how combining multiple trees improves accuracy and reduces overfitting.

    Open on YouTube
  5. Lesson 10: Support Vector Machine - How Support Vector Machine Works | SVM In Machine Learning | Simplilearn

    Support Vector Machines (SVM) are covered, including how they find the best boundary between classes. The video includes practical examples.

    Open on YouTube
  6. Lesson 11: Naive Bayes Classifier | Naive Bayes Algorithm | Naive Bayes Classifier With Example | Simplilearn

    Naive Bayes classifier is explained with examples. It's a probabilistic algorithm useful for text classification and other tasks.

    Open on YouTube
  7. Lesson 12: KNN Algorithm In Machine Learning | KNN Algorithm Using Python | K Nearest Neighbor | Simplilearn

    K-Nearest Neighbors (KNN) is introduced as a simple, instance-based learning method. The video shows how to implement KNN in Python.

    Open on YouTube
  8. Lesson 13: K Means Clustering Algorithm | K Means In Python | Machine Learning Algorithms |Simplilearn

    K-Means clustering, an unsupervised algorithm, is covered. It explains how to group data points into clusters and includes a Python demo.

    Open on YouTube
  9. Lesson 14: Cost Function In Machine Learning With Example | Machine Learning Tutorial | Simplilearn

    This video explains the cost function, a key concept in training machine learning models. It shows how cost functions measure model error.

    Open on YouTube

Section 3: Career Guidance and Interview Prep

  1. Lesson 15: How to Become A Machine Learning Engineer | How To Learn Machine Learning | Simplilearn

    Career advice on becoming a machine learning engineer. It outlines the skills and learning path needed for this role.

    Open on YouTube
  2. Lesson 16: Machine Learning Engineer Salary, Roles And Responsibilities, Skills and Resume | Simplilearn

    Details on machine learning engineer salary, roles, responsibilities, and resume tips. It gives a realistic view of the job market.

    Open on YouTube
  3. Lesson 17: Machine Learning Interview Questions & Answers | Machine Learning Interview Preparation |Simplilearn

    A long video with common machine learning interview questions and answers. It's useful for interview preparation and reinforcing concepts.

    Open on YouTube
  4. Lesson 18: Tips To Learn Python Programming | Effective Tips To Learn Python Faster | Simplilearn

    Tips to learn Python programming faster. It offers practical advice for beginners to improve their coding skills.

    Open on YouTube

Section 4: Extended Learning and Projects

  1. Lesson 19: Machine Learning Algorithms Full Course | Machine Learning Algorithms Explained | Simplilearn

    A full course on machine learning algorithms, covering many algorithms in depth. It's a comprehensive resource for solidifying your understanding.

    Open on YouTube
  2. Lesson 20: Supervised And Unsupervised Machine Learning Full Course - Algorithms With Examples | Simplilearn

    A full course on supervised and unsupervised learning with examples. It expands on the core concepts and provides more context.

    Open on YouTube
  3. Lesson 21: IPL Data Analysis Using Python | IPL Data Analysis 2026 | Data Analysis Project | Simplilearn

    A hands-on project analyzing IPL cricket data using Python. It demonstrates data analysis and visualization with real data.

    Open on YouTube
  4. Lesson 22: Python Full Course 2026 | Python Basics to Advanced Course in 24 Hours | Python Course | Simplilearn

    A 24-hour Python course covering basics to advanced topics. It's a thorough resource for building strong Python skills.

    Open on YouTube
  5. Lesson 23: AI and Machine Learning Full Course 2026 | AI & Machine Learning Tutorial For Beginners |Simplilearn

    A full course on AI and machine learning for beginners. It covers a wide range of topics, from basics to advanced concepts.

    Open on YouTube
  6. Lesson 24: Machine Learning Full Course 2026 | Complete Machine Learning Training in 24 Hours | Simplilearn

    A complete machine learning training course in 24 hours. It's a comprehensive wrap-up of the playlist's content.

    Open on YouTube

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