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University & Pro Programs

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Master Artificial Intelligence
18 coding exercises 3 projects
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Master Data Science & Machine Learning in Python
136 coding exercises 6 projects
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Master Python programming
51 coding exercises 3 projects
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Machine Learning Essentials with Python
1 coding exercise 1 project

Free Machine Learning Courses

img icon BASICS
NEW
Data Preparation for Machine Learning
star   4.49 7.2K+ learners 1 hr

Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

img icon BASICS
Python for Machine Learning
star   4.51 469.8K+ learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

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Python Libraries for Machine Learning
star   4.55 10K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

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NumPy Tutorial
star   4.5 15.5K+ learners 1 hr

Skills: Numpy Scalar Functions,Numpy Mathematical Operations,Numpy Arrays,Numpy joining, intersection, and difference,Numpy Matrix Calculations

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Python Pandas
star   4.34 22.6K+ learners 1.5 hrs

Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations

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Uses of Pandas
star   4.49 2.7K+ learners 1 hr

Skills: Pandas , Uses of Pandas, Functions in Pandas

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Introduction to Scikit Learn
star   4.33 5.6K+ learners 1.5 hrs

Skills: Scikit learn, Installing Scikit learn

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SciPy in Python
star   4.4 3.6K+ learners 1 hr

Skills: Introduction to SciPy, Installing SciPy, Sub Packages in SciPy, SciPy Clusters, SciPy Constants, SciPy FFTPack, SciPy Interpolation, SciPy Linalg, SciPy Ndimage

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Data Visualization using Python
star   4.55 85K+ learners 2 hrs

Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Basics of Machine Learning
star   4.39 147.4K+ learners 2.5 hrs

Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

free icon BASICS
Data Preparation for Machine Learning
star   4.49 7.2K+ learners 1 hr

Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

free icon BASICS
Python for Machine Learning
star   4.51 469.8K+ learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

free icon BASICS
Python Libraries for Machine Learning
star   4.55 10K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

free icon BASICS
NumPy Tutorial
star   4.5 15.5K+ learners 1 hr

Skills: Numpy Scalar Functions,Numpy Mathematical Operations,Numpy Arrays,Numpy joining, intersection, and difference,Numpy Matrix Calculations

free icon BASICS
Python Pandas
star   4.34 22.6K+ learners 1.5 hrs

Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations

free icon BASICS
Uses of Pandas
star   4.49 2.7K+ learners 1 hr

Skills: Pandas , Uses of Pandas, Functions in Pandas

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Google Gemini Practical AI for Working Professionals
free icon BASICS
Introduction to Scikit Learn
star   4.33 5.6K+ learners 1.5 hrs

Skills: Scikit learn, Installing Scikit learn

free icon BASICS
SciPy in Python
star   4.4 3.6K+ learners 1 hr

Skills: Introduction to SciPy, Installing SciPy, Sub Packages in SciPy, SciPy Clusters, SciPy Constants, SciPy FFTPack, SciPy Interpolation, SciPy Linalg, SciPy Ndimage

free icon BASICS
Data Visualization using Python
star   4.55 85K+ learners 2 hrs

Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

free icon BASICS
Basics of Machine Learning
star   4.39 147.4K+ learners 2.5 hrs

Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

Learn Machine Learning for Free

These free machine learning courses online give you a practical learning path from data preparation to model building with Python. You learn how to prevent data leakage, balance datasets, and use k-fold cross-validation, then build strong fundamentals with NumPy arrays and operations, Pandas dataframes, and core data manipulation. You also strengthen EDA and visualization skills using Matplotlib, Seaborn, Plotly, SciPy, and scikit learn, backed by statistics and probability for better evaluation.

Starting with data preparation, you will learn data leakage checks, data balancing, and k-fold cross-validation, then use NumPy and Pandas for data manipulation and exploration. You will build a strong foundation in statistics and probability, then train models such as linear regression, logistic regression, Naive Bayes, decision trees, random forests, SVMs, and k-means clustering using scikit learn. You will also learn visualization with Matplotlib, Seaborn, and Plotly, work with SciPy tools, complete prediction and EDA projects, and deploy a model using Flask, building skills that prepare you for neural networks, natural language processing, and TensorFlow workflows.

Skills You’ll Gain in These Best Free Machine Learning Courses 

  • Machine Learning Algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines.

  • Programming and Libraries: Python, NumPy, Pandas, scikit learn, and TensorFlow.

  • Modeling and Evaluation: Data preprocessing, Model training, Model validation, and Performance evaluation metrics.

  • Project and Delivery Skills: Build and test machine learning models, Iterate and improve model performance.

  • Core Foundations: Neural networks fundamentals, and Natural language processing fundamentals.
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Get started with these courses

img icon BASICS
Artificial Intelligence and Machine Learning Projects
star   4.44 4.1K+ learners 1.5 hrs

Skills: Machine Learning Algorithms

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Machine Learning Projects
star   4.5 3.2K+ learners 1.5 hrs

Skills: Exploratory Data Analysis, Machine Learning Algorithms

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Exploratory Data Analysis Projects
star   4.5 2K+ learners 2.5 hrs

Skills: Data Visualisation, Analysing the Data

img icon BASICS
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Data Preparation for Machine Learning
star   4.49 7.2K+ learners 1 hr

Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Predicting Fleet Failure in Car Rental Company
653 learners 1 hr

Skills: Prediction Modeling Techniques, Exploratory Data Analysis

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Application of Classification Algorithms
star   4.75 1.4K+ learners 1.5 hrs

Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree

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Model Deployment in R
1.5K+ learners 1 hr

Skills: Model Deployment Architecture, Model Deployment Process, Hands-on

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Random Forest Regression
star   4.49 1.5K+ learners 1 hr

Skills: Random Forest Regression, Hands-on, Logistic Regression vs Random Forest , Linear Regression vs Random Forest

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Machine Learning Landscape
star   4.64 3.9K+ learners 1.5 hrs

Skills: Machine Learning Landscape

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Bagging and Boosting
star   4.62 2K+ learners 1 hr

Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python

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Machine Learning Modelling
star   4.62 4.8K+ learners 2.5 hrs

Skills: Linear Regression, Logistic Regression, Naïve Bayes

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Bias Variance Tradeoff
star   4.59 1.2K+ learners 0.5 hr

Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?

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Inferential Statistics
star   4.56 4.8K+ learners 1 hr

Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA

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Supervised Machine Learning with Tree Based Models
star   4.56 9.8K+ learners 2 hrs

Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms

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Sensitivity Analysis
star   4.55 1.7K+ learners 1 hr

Skills: Introduction to Sensitivity Analysis, Types of Sensitivity Analysis, How Does Sensitivity Analysis Work?, Key Applications of Sensitivity Analysis, Advantages and Disadvantages, Practical Demonstration in Python

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Basics of EDA with Python
star   4.55 12.7K+ learners 2 hrs

Skills: Practical visualization walkthrough, IPL data analysis with Python

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Python for Machine Learning
star   4.51 469.8K+ learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

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Basics of Machine Learning
star   4.39 147.4K+ learners 2.5 hrs

Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

img icon BASICS
Data Visualization using Python
star   4.55 85K+ learners 2 hrs

Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Python Project Development
star   4.36 54.8K+ learners 1 hr

Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data

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Statistics for Machine Learning
star   4.58 43.6K+ learners 2 hrs

Skills: Descriptive Statistics, Measures of Dispersion Range and IQR,,Central Tendency and 3 Ms,The Empirical Rule and Chebyshev Rule,Correlation Analysis

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Machine Learning Algorithms
star   4.49 32.1K+ learners 1.5 hrs

Skills: Classification (Logistic Regression, Decision Trees, SVM), Regression (Linear, Ridge, Lasso), Clustering (K-means, Hierarchical), model evaluation, cross validation

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Organizational Behaviour
star   4.49 26.3K+ learners 1 hr

Skills: Communication, Interpersonal & Team Collaboration, Leadership & Influence, Motivation, Conflict Resolution, Organizational Analysis, Change Management, Decision-Making, Emotional Intelligence.

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Python Pandas
star   4.34 22.6K+ learners 1.5 hrs

Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations

New

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Artificial Intelligence and Machine Learning Projects
star   4.44 4.1K+ learners 1.5 hrs

Skills: Machine Learning Algorithms

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Machine Learning Projects
star   4.5 3.2K+ learners 1.5 hrs

Skills: Exploratory Data Analysis, Machine Learning Algorithms

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Exploratory Data Analysis Projects
star   4.5 2K+ learners 2.5 hrs

Skills: Data Visualisation, Analysing the Data

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star   4.49 7.2K+ learners 1 hr

Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Predicting Fleet Failure in Car Rental Company
653 learners 1 hr

Skills: Prediction Modeling Techniques, Exploratory Data Analysis

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Application of Classification Algorithms
star   4.75 1.4K+ learners 1.5 hrs

Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree

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Model Deployment in R
1.5K+ learners 1 hr

Skills: Model Deployment Architecture, Model Deployment Process, Hands-on

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Random Forest Regression
star   4.49 1.5K+ learners 1 hr

Skills: Random Forest Regression, Hands-on, Logistic Regression vs Random Forest , Linear Regression vs Random Forest

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star   4.64 3.9K+ learners 1.5 hrs

Skills: Machine Learning Landscape

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Bagging and Boosting
star   4.62 2K+ learners 1 hr

Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python

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Machine Learning Modelling
star   4.62 4.8K+ learners 2.5 hrs

Skills: Linear Regression, Logistic Regression, Naïve Bayes

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Bias Variance Tradeoff
star   4.59 1.2K+ learners 0.5 hr

Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?

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Inferential Statistics
star   4.56 4.8K+ learners 1 hr

Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA

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Supervised Machine Learning with Tree Based Models
star   4.56 9.8K+ learners 2 hrs

Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms

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Sensitivity Analysis
star   4.55 1.7K+ learners 1 hr

Skills: Introduction to Sensitivity Analysis, Types of Sensitivity Analysis, How Does Sensitivity Analysis Work?, Key Applications of Sensitivity Analysis, Advantages and Disadvantages, Practical Demonstration in Python

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Basics of EDA with Python
star   4.55 12.7K+ learners 2 hrs

Skills: Practical visualization walkthrough, IPL data analysis with Python

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Python for Machine Learning
star   4.51 469.8K+ learners 1.5 hrs

Skills: NumPy Arrays, NumPy Operations, NumPy Math, Saving & Loading NumPy, Pandas Series, Pandas DataFrame, Pandas Functions (Mean, Median, Max, Min), Data Manipulation, Supervised Learning, Unsupervised Learning, Machine Learning with Python

img icon BASICS
Basics of Machine Learning
star   4.39 147.4K+ learners 2.5 hrs

Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

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Data Visualization using Python
star   4.55 85K+ learners 2 hrs

Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Python Project Development
star   4.36 54.8K+ learners 1 hr

Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data

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Statistics for Machine Learning
star   4.58 43.6K+ learners 2 hrs

Skills: Descriptive Statistics, Measures of Dispersion Range and IQR,,Central Tendency and 3 Ms,The Empirical Rule and Chebyshev Rule,Correlation Analysis

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Machine Learning Algorithms
star   4.49 32.1K+ learners 1.5 hrs

Skills: Classification (Logistic Regression, Decision Trees, SVM), Regression (Linear, Ridge, Lasso), Clustering (K-means, Hierarchical), model evaluation, cross validation

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star   4.49 26.3K+ learners 1 hr

Skills: Communication, Interpersonal & Team Collaboration, Leadership & Influence, Motivation, Conflict Resolution, Organizational Analysis, Change Management, Decision-Making, Emotional Intelligence.

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Python Pandas
star   4.34 22.6K+ learners 1.5 hrs

Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations

Our learners also choose

Learner reviews of the Free Machine Learning Courses

Our learners share their experiences of our courses

4.48
68%
23%
6%
1%
2%
Reviewer Profile

5.0

“Engaging and Informative Machine Learning Course”
The curriculum was well-structured and covered a wide range of topics, from the basics of machine learning to more advanced techniques. I particularly appreciated the focus on practical applications and the use of real-world datasets. The quizzes and assignments were challenging but fair, and they helped me to solidify my understanding of the material. Overall, I found the course to be both enjoyable and informative, and I would highly recommend it to anyone interested in learning more about machine learning.
Reviewer Profile
Ameer Hamza

5.0

“Great Insights on How We Prepare Data for Machine Learning”
Great insights on preparing data for Machine Learning: Learned essential data cleaning, transformation, and preprocessing techniques. This will enable us to work and grow significantly in the field of Data Science. I would love to come back in the future, maybe to have an overview again!
Reviewer Profile
Muhammad Naeem 👨‍💻 (Data Scientist)

5.0

“Completed a Comprehensive Course on Preparing Data for Machine Learning”
Completed a comprehensive course on Preparing Data for Machine Learning, gaining hands-on experience in data cleaning, feature engineering, and handling missing values to enhance model performance and accuracy.
Reviewer Profile

5.0

Country Flag India
“Learn Data Preparation for ML Models with Ease”
I liked how the instructor used examples to explain the concepts in the videos and the clarity he has on topics.
Reviewer Profile

5.0

Country Flag India
“The Quiz is Really Interesting and the Lectures are Easy to Follow”
I really enjoyed the engaging course path with the quiz, which is easy to follow.
Reviewer Profile

4.0

Country Flag India
“Very Helpful for My Studies and My Future Career”
I like the course depth and it's very clear to understand. The instructor teaches very well. Thank you for a great learning platform.
Reviewer Profile

5.0

Country Flag India
“Understanding of Preparing Data for Machine Learning”
This free course was very helpful because it was easy to learn and understand. The materials provided were easily understandable.
Reviewer Profile

5.0

Country Flag India
“It Was an Excellent Course for Beginners. I Like the Lecture Delivery and the Case Study as Well”
It was always a good experience with great learning to learn new tools and courses. I personally advise using this platform to enhance your skills.
Reviewer Profile

5.0

Country Flag India
“Completely Understandable and Good Explanation”
Teaching, content, theory, and practice. Everything was good, starting from data preparation to building the model.
Reviewer Profile

5.0

“The Python Course Was Well-Structured and Informative, Offering Clear Explanations That Enhanced My Programming Skills Effectively”
The Python course exceeded my expectations with its comprehensive content and engaging format. The instructor provided clear explanations and practical examples, which made complex concepts easy to understand. The hands-on exercises reinforced my learning, allowing me to apply my skills effectively. Overall, it was an enriching experience that significantly boosted my programming confidence.

Meet your faculty

Meet industry experts who will teach you relevant skills in artificial intelligence

instructor img

Mr. Bharani Akella

Data Scientist
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.
instructor img

Mr. Bharani Akella

Data Scientist
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.
instructor img

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • 30+ years of experience in data science, ML, and analytics.
  • Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
instructor img

Dr. Abhinanda Sarkar

Senior Faculty & Director Academics, Great Learning
  • 30+ years of experience in data science, ML, and analytics.
  • Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
instructor img

Dr. Sunil Kumar

GM - Engineering Innovation
  • 15+ years of industry experience in AI, machine learning, NLP
  • Published researcher, speaker, and author of 'R Machine Learning Projects
instructor img

Prof. Mukesh Rao

Senior Faculty, Academics, Great Learning
  • 20+ years of expertise in AI, machine learning, and analytics
  • Director - Academics at Great Learning

Frequently Asked Questions

What will I learn in these free machine learning courses?

These free Machine Learning courses online provide a comprehensive foundation in AI and data science. You will cover core concepts such as supervised, unsupervised, and reinforcement learning. Specifically, you will gain hands-on experience with algorithms like linear and logistic regression, decision trees, random forests, and k-means clustering. This structured approach makes them the best free machine learning courses for those wanting to bridge the gap between theory and real-world application.

Are these free machine learning courses online suitable for complete beginners?

Yes. We offer a best free machine learning course for beginners that starts with basic Python programming and essential statistics. You don't need a heavy coding background to start; the curriculum is designed to guide you from the ground up, making these free courses in machine learning accessible to students and career-switchers alike.

What specific technical skills will I gain from these free ml courses?

By enrolling in these free ml courses, you will acquire high-demand skills, including:

  • Data Preprocessing: Cleaning and structuring raw data for model training.

  • Supervised Learning: Building predictive models for classification and regression.

  • Unsupervised Learning: Discovering hidden patterns through clustering and dimensionality reduction.

  • Deep Learning: An introduction to neural networks and computer vision.

  • Model Evaluation: Using metrics like accuracy, precision, recall, and F1-score to tune performance.


Will I have lifetime access to these free Machine Learning courses with certificates?

Yes. You will have lifetime access to these courses after enrolling in them and access to certificates after completing the course.  

Which tools and libraries are covered in the curriculum?

Our free machine learning courses online focus on industry-standard tools. You will learn to use Python as your primary language, along with powerful libraries such as NumPy and Pandas for data manipulation, Matplotlib and Seaborn for visualization, and Scikit-learn for implementing advanced ML algorithms.

Will I get a certificate after completing these free Machine Learning courses?

All courses are free, A certificate is available for a nominal fee upon successful completion of the course. 

How long does it take to complete these free machine learning courses online?

Most of our high-impact modules range from 1.5 to 3 hours of video content. This "sprint-style" learning allows you to gain a specific, marketable skill, making these the best free machine learning courses for busy professionals.

How much do these free Machine Learning courses cost Online?

These are free courses; you can enroll and learn for free online.  

Are the free machine learning courses self-paced?

Yes. Every course in the academy is entirely self-paced. Once you sign up, you get lifetime access to the video lectures and reading materials. This flexibility is perfect for anyone looking for free machine learning courses online that can be completed alongside a full-time job or university studies.

Do these courses include hands-on projects?

Absolutely. Practical application is a core focus. You will work on real-world datasets to solve problems such as predicting house prices, detecting fraudulent transactions, and segmenting customers for marketing. This hands-on experience ensures that our free courses in machine learning provide more than just theoretical knowledge.

Is there a specific machine learning course for healthcare or finance?

While the foundational courses are broad, the techniques you learn, such as predictive modeling and anomaly detection, are directly applicable to these sectors. Many learners use these free ml courses as a springboard to specialized roles in medical diagnostics or financial risk analysis.

Can I take multiple free ml courses at the same time?

Yes. You can enroll in as many courses as you wish. Many students choose to take a Python course alongside a Linear Regression module to strengthen their programming and mathematical foundations simultaneously.

Why take Machine Learning free courses from Great Learning Academy?

Great Learning Academy offers a wide range of high-quality, completely free Machine Learning courses. From beginner to advanced level, these free courses are designed to help you improve your Machine Learning and technology-related skills and achieve your goals. All these courses come with a certificate of completion, so you can demonstrate your new skills to the world. Start learning today and discover the benefits of free Machine Learning courses!



 

Who are eligible to take these free Machine Learning courses?

These courses have no prerequisites. Anybody can learn from these courses for free online. 


 

What are the steps to enroll in these free Machine Learning courses?

To learn Machine Learning basics and advanced concepts from these courses, you need to,

  1. Go to the course page
  2. Click on the "Enroll for Free" button
  3. Start learning the Machine Learning course for free online.