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Machine Learning with Python Free Course

★ 4.7/5
Google Reviews
★ 4.7/5
ScholarHat Reviews
37
Videos
4.9
Rating
Free
100% Free
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Free Machine Learning with Python Course Overview

Welcome to the Free Machine Learning with Python Course! This beginner-friendly course introduces you to the exciting world of Artificial Intelligence and data-driven decision making using Python, one of the most popular programming languages for machine learning.

Machine Learning empowers systems to learn from data, identify patterns, and make predictions. Through this course, you'll learn ML fundamentals step by step and gain practical skills to build intelligent models for real-world applications.

What You’ll Learn in This Free Machine Learning Course

Understand Machine Learning fundamentals and core concepts
Learn popular ML algorithms, models, and workflows
Understand data preprocessing, feature engineering, and model evaluation
Gain practical experience with hands-on projects using Python libraries
Prepare to build intelligent systems and start your AI journey

Why Choose This Free Machine Learning Course?

100% free and beginner-friendly learning path
 Step-by-step lessons with examples and practical exercises
Earn a certificate of completion to showcase your ML skills
Build real-world projects to kickstart your AI and Data Science career

Why Learn Machine Learning with Python?

  1. Industry Demand: Machine Learning skills are highly sought after across industries as organizations increasingly rely on data-driven decision-making and automation.
  2. Versatility: Applicable in diverse sectors such as healthcare, finance, e-commerce, marketing, cybersecurity, and robotics.
  3. Powerful Ecosystem: Python offers a rich collection of ML libraries and frameworks like NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch for building intelligent solutions.
  4. Efficiency & Automation: Learn how to create models that automate predictions, pattern detection, and decision processes, saving time and resources.
  5. Future-Ready Skill: Stay relevant in the evolving tech landscape as AI and machine learning continue to transform modern industries.

Top Career Options After Learning Machine Learning with Python

  1. Machine Learning Engineer: Design, build, and deploy machine learning models for real-world applications.
  2. Data Scientist: Analyze data, develop predictive models, and generate insights to support decision-making.
  3. AI Engineer: Create intelligent systems using ML algorithms, deep learning, and automation techniques.
  4. Python Developer: Develop data-driven applications and integrate machine learning solutions into software systems.
  5. Research Analyst: Apply statistical analysis and machine learning methods to solve business or scientific problems.
  6. Data Analyst: Use Python-based ML libraries to uncover trends, visualize data, and support strategic planning.

Tools for Learning AWS

  1. Python Programming Environment: Write and execute ML code using tools like Jupyter Notebook, Google Colab, or local IDEs such as VS Code and PyCharm.
  2. NumPy & Pandas: Perform numerical computations, data manipulation, and preprocessing efficiently.
  3. Scikit-learn: Build and evaluate machine learning models with ready-to-use algorithms for classification, regression, and clustering.
  4. TensorFlow & PyTorch: Develop advanced deep learning models for tasks like image recognition, NLP, and neural networks.
  5. Visualization Libraries: Use Matplotlib and Seaborn to analyze data patterns and present insights visually.
  6. Datasets & APIs: Access real-world datasets from platforms like Kaggle or open data APIs for hands-on practice and experimentation.

Features

Course Features: Free Machine Learning with Python Course

  1. Beginner-Friendly Curriculum: Ideal for beginners entering the world of AI and data science, with concepts explained in simple, easy-to-follow modules.
  2. Structured Learning Path: Progress through well-organized lessons that gradually build your understanding of machine learning concepts.
  3. Interactive Video Lectures: Learn through engaging sessions that blend theory, coding demonstrations, and real-world examples.
  4. Core ML Topics Covered: Explore data preprocessing, supervised and unsupervised learning, model evaluation, feature engineering, and popular Python libraries like NumPy, Pandas, Matplotlib, and Scikit-learn.
  5. Certification Upon Completion: Earn a certificate to showcase your machine learning and Python skills to potential employers.
  6. Flexible Learning Schedule: Study anytime, anywhere at your own pace, making it perfect for students and working professionals.
This course includes
100 % OFF
₹ 1,770 Free

Included in this Course

Introduction To Ai & Machine Learning
Machine Learning Introduction
Preview 10m 42s
Introduction To Machine Learning
Preview 05m 08s
Why Machine Learning
Preview 10m 26s
Main Challenges of Machine Learning
07m 04s
More Challenges in Machine Learning
04m 00s

Ames House Pricing Project
Ames House Pricing Project Overview
06m 30s
How Machine Learning Project Works
11m 19s
Setting Up IDE and DataSet
11m 01s
Traditional Vs Uv Workflow
05m 29s
Setup Building
07m 34s

Building The Ai
Hist Plot On Sales
10m 03s
Exploring Neighborhood Feature
05m 07s
Correlation In Ml
10m 25s
Prepared Data
01m 28s
Reading Output
05m 10s
Combining Data
05m 18s
New Correlation Matrix
06m 43s

Testing Our Ai Model
Testing Our Model
03m 56s
Cleaning Our Data
07m 38s
Fixing Problem Occurred While Cleaning The Data
06m 34s
Converting Textual Data Into Numbers
05m 10s
Feature Scaling
08m 54s
Predicting House Prices
11m 05s
Decision Tree
07m 21s
Random Forest Regression
15m 22s

Tuning Our Ai Model
Tunning Hyper Parameters
04m 43s
Grid Search CV
05m 38s
Random Search CV
04m 11s
Interpreting using Feature Importance
13m 57s
Doing Predictions
02m 35s

Classification of Data
Entry Into Classification Model
07m 30s
Classification Model
08m 59s
Classification Model 2
09m 35s
Confusion Matrix
11m 15s
Roc Curve
09m 21s
Working With Test Data
09m 21s
Multi Class Classification
Multi Class Classification
12m 15s
Mentor-led Career Bootcamp

Multi-Cloud .NET AI & Agentic AI Architect Bootcamp

Go from learning to job-ready — live doubt sessions, real projects, hands-on labs and interview prep.

Explore this Bootcamp
Multi-Cloud .NET AI & Agentic AI Architect Bootcamp
What's inside
15 Doubt Sessions
6 Projects
15 Weeks
64 Labs
578 Lessons
4.8 Rating
This course includes
100 % OFF
₹ 1,770 Free

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Frequently Asked Questions

Q1. Are these coding courses really 100% free?
Yes! All our listed courses are completely free. You can access all learning materials, videos, and resources without paying a single rupee.
Q2. Who can join these free programming courses?
Anyone! Whether you're a beginner with no coding experience or someone looking to upskill, our courses are designed for all levels.
Q3. Are these courses beginner-friendly?
Absolutely. Every course includes step-by-step guidance, real-life examples, and practice projects to help you learn effectively from scratch.
Q4. Are the free courses self-paced?
Yes, all our courses are fully self-paced. You can learn anytime, anywhere, and from any device that suits you.
Q5. Will these courses help me get a job?
Our focus is on job-ready skills. The courses are built to teach industry-relevant knowledge that employers value, including hands-on coding and real-world projects.
Q6. Can I get career advice or help with interviews?
Yes! Along with courses, we offer career resources like interview prep eBooks, resume tips, and mock interview support.
Q7. Will learning from free courses be enough to get a developer job?
While free courses provide strong fundamentals, combining them with real-world projects, internships, and advanced practice can significantly boost your chances of landing a job.
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