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Free Machine Learning Courses
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Free Machine Learning Courses
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Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.
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Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building
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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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Skills: Numpy, Pandas, Matplotlib, SeaBorn
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Skills: Numpy Scalar Functions,Numpy Mathematical Operations,Numpy Arrays,Numpy joining, intersection, and difference,Numpy Matrix Calculations
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Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations
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Skills: Pandas , Uses of Pandas, Functions in Pandas
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Skills: Scikit learn, Installing Scikit learn
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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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Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly
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Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant
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Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data
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Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.
View Course
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building
View Course
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
View Course
Skills: Numpy, Pandas, Matplotlib, SeaBorn
View Course
Skills: Numpy Scalar Functions,Numpy Mathematical Operations,Numpy Arrays,Numpy joining, intersection, and difference,Numpy Matrix Calculations
View Course
Skills: Introduction to Pandas and DataFrames, Usage of DataFrames, DataFrame methods and operations, Selecting and Indexing operations, Aggregation operations
View Course
Skills: Pandas , Uses of Pandas, Functions in Pandas
View Course
Skills: Scikit learn, Installing Scikit learn
View Course
Skills: Introduction to SciPy, Installing SciPy, Sub Packages in SciPy, SciPy Clusters, SciPy Constants, SciPy FFTPack, SciPy Interpolation, SciPy Linalg, SciPy Ndimage
View Course
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly
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Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant
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Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data
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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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Skills: Machine Learning Algorithms
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Skills: Predictive Analytics, Feature Engineering, Deep Feature Synthesis, Model Selection Techniques
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Skills: Introduction to Feature Engineering, Under sampling, Over sampling
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Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building
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Skills: Prediction Modeling Techniques, Exploratory Data Analysis
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Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree
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Skills: Model Deployment Architecture, Model Deployment Process, Hands-on
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Skills: Random Forest Regression, Hands-on, Logistic Regression vs Random Forest , Linear Regression vs Random Forest
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Skills: Machine Learning Landscape
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Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python
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Skills: Linear Regression, Logistic Regression, Naïve Bayes
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Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?
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Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA
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Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms
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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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Skills: Practical visualization walkthrough, IPL data analysis with Python
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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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Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant
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Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly
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Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.
View Course
Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data
View Course
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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Skills: Classification (Logistic Regression, Decision Trees, SVM), Regression (Linear, Ridge, Lasso), Clustering (K-means, Hierarchical), model evaluation, cross validation
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Skills: Communication, Interpersonal & Team Collaboration, Leadership & Influence, Motivation, Conflict Resolution, Organizational Analysis, Change Management, Decision-Making, Emotional Intelligence.
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New
Skills: Machine Learning Algorithms
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Skills: Predictive Analytics, Feature Engineering, Deep Feature Synthesis, Model Selection Techniques
View Course
Skills: Introduction to Feature Engineering, Under sampling, Over sampling
View Course
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building
View Course
Skills: Prediction Modeling Techniques, Exploratory Data Analysis
View Course
Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree
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Skills: Model Deployment Architecture, Model Deployment Process, Hands-on
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Skills: Random Forest Regression, Hands-on, Logistic Regression vs Random Forest , Linear Regression vs Random Forest
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Trending
Skills: Machine Learning Landscape
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Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python
View Course
Skills: Linear Regression, Logistic Regression, Naïve Bayes
View Course
Skills: Bias, Variance, Trade-off, How to avoid overfitting and underfitting?
View Course
Skills: Data Collection, Statistical Analysis, Probability, Central Limit Theorem, Hypothesis Testing, Chi-Square Test, ANOVA
View Course
Skills: Scikit Learn Library, Decision Tree, Random Forest, Demonstration for Algorithms
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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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Skills: Practical visualization walkthrough, IPL data analysis with Python
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Popular
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
View Course
Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant
View Course
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly
View Course
Skills: Learn the fundamentals of machine learning, including supervised and unsupervised learning, regression, and recommendation systems. Join this free machine learning course to apply these skills in real-world business scenarios.
View Course
Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data
View Course
Skills: Descriptive Statistics, Measures of Dispersion Range and IQR,,Central Tendency and 3 Ms,The Empirical Rule and Chebyshev Rule,Correlation Analysis
View Course
Skills: Classification (Logistic Regression, Decision Trees, SVM), Regression (Linear, Ridge, Lasso), Clustering (K-means, Hierarchical), model evaluation, cross validation
View Course
Skills: Communication, Interpersonal & Team Collaboration, Leadership & Influence, Motivation, Conflict Resolution, Organizational Analysis, Change Management, Decision-Making, Emotional Intelligence.
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Learner reviews of the Free Machine Learning Courses
Our learners share their experiences of our courses
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Meet your faculty
Meet industry experts who will teach you relevant skills in artificial intelligence
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30+ years of experience in data science, ML, and analytics.
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Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
Mr. Bharani Akella
Mr. Bharani Akella
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30+ years of experience in data science, ML, and analytics.
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Ph.D. from Stanford, taught at MIT, ISI, and IIM Bangalore.
Dr. Sunil Kumar
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15+ years of industry experience in AI, machine learning, NLP
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Published researcher, speaker, and author of 'R Machine Learning Projects
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,
- Go to the course page
- Click on the "Enroll for Free" button
- Start learning the Machine Learning course for free online.
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