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University Programs

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2 Years  • Online

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14 Weeks  • Online

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Johns Hopkins University

16 weeks  • Online

Free Supervised Machine Learning Courses

BASICS
Introduction to Machine Learning
star   4.46 78K+ Learners 1 hr

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.

BASICS
Data Preparation for Machine Learning
star   4.49 7.5K+ Learners 1 hr

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

BASICS
Python for Machine Learning
star   4.51 475K+ 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

BASICS
Python Libraries for Machine Learning
star   4.55 10.2K+ Learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

BASICS
Basics of Machine Learning
star   4.39 149.5K+ Learners 2.5 hrs

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

BASICS
Machine Learning Algorithms
star   4.49 32.5K+ Learners 1.5 hrs

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

BASICS
Supervised Machine Learning Tutorial
star   4.43 2.4K+ Learners 1 hr

Skills: Supervised Machine Learning, Linear Regression, Characteristics of Supervised Machine Learning

BASICS
Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.9K+ Learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

BASICS
Logistic Regression on Customer Data
star   4.5 3.2K+ Learners 1 hr

Skills: Logistic Regression on Customer Data

BASICS
Supervised Machine Learning with Tree Based Models
star   4.56 9.9K+ Learners 2 hrs

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

BASICS
Decision Tree
star   4.43 3.6K+ Learners 1.5 hrs

Skills: Entropy, Heterogeneity, Shannon's Entropy, Preventing Overfitting

BASICS
Support Vector Machines
star   4.53 3.2K+ Learners 1 hr

Skills: Introduction to Machine Learning, Kernel Functions, SVM Demo in Python

free icon BASICS
Introduction to Machine Learning
star   4.46 78K+ Learners 1 hr

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.

free icon BASICS
Data Preparation for Machine Learning
star   4.49 7.5K+ Learners 1 hr

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

free icon BASICS
Python for Machine Learning
star   4.51 475K+ 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 10.2K+ Learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

free icon BASICS
Basics of Machine Learning
star   4.39 149.5K+ Learners 2.5 hrs

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

free icon BASICS
Machine Learning Algorithms
star   4.49 32.5K+ Learners 1.5 hrs

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

free icon BASICS
Supervised Machine Learning Tutorial
star   4.43 2.4K+ Learners 1 hr

Skills: Supervised Machine Learning, Linear Regression, Characteristics of Supervised Machine Learning

free icon BASICS
Supervised Machine Learning with Logistic Regression and Naïve Bayes

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

free icon BASICS
Logistic Regression on Customer Data
star   4.5 3.2K+ Learners 1 hr

Skills: Logistic Regression on Customer Data

free icon BASICS
Supervised Machine Learning with Tree Based Models

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

free icon BASICS
Decision Tree
star   4.43 3.6K+ Learners 1.5 hrs

Skills: Entropy, Heterogeneity, Shannon's Entropy, Preventing Overfitting

free icon BASICS
Support Vector Machines
star   4.53 3.2K+ Learners 1 hr

Skills: Introduction to Machine Learning, Kernel Functions, SVM Demo in Python

Learn Supervised Machine Learning & Get Completion Certificates

Supervised machine learning is a vital subset of artificial intelligence that teaches algorithms to predict or make decisions from tagged training data. It involves guiding the algorithm with explicit feedback, mimicking a teacher-student learning relationship. This allows the model to extrapolate from training data to make accurate predictions on new data.

 

Key Highlights of Our Free Supervised Machine Learning Courses Collection

  • Foundational and Advanced Topics: The courses cover basic and intricate aspects of supervised learning, including classification and regression techniques.
  • Practical Applications: Explore real-world applications in various fields such as healthcare, finance, and marketing.
  • Comprehensive Learning: From data preparation to model evaluation, understand every step in the supervised machine learning pipeline.

 

Skills Covered

  • Pattern Recognition: Learn to identify patterns and relationships between input features and target variables.
  • Model Building: Gain expertise in constructing models for classification (categorizing data points) and regression (predicting continuous values).
  • Algorithm Application: Master the use of major algorithms, such as decision trees, neural networks, support vector machines, and more.
  • Performance Evaluation: Develop skills in assessing model accuracy using metrics like precision, recall, and F1 score.

 

Who Should Take Our Free Supervised Machine Learning Courses?

This course is designed for aspiring data scientists, AI specialists, and professionals who want to enhance their predictive analytics capabilities. It also suits students and researchers interested in applying machine learning to solve practical problems.

 

What Will You Learn in Free Supervised Machine Learning Courses?

  • Core Concepts: Understand the essentials of supervised learning, from data labeling to model optimization.
  • Classification Techniques: Learn to classify data into predefined categories using various algorithms.
  • Regression Methods: Explore how to predict numerical values using regression models.
  • Real-world Applications: Discover how supervised learning is applied in diverse industries to solve specific challenges.
  • Model Optimization: Get hands-on experience in refining machine learning models to enhance their accuracy and efficiency.

 

By the end of these courses, participants will be equipped to implement supervised machine learning models effectively, making them valuable assets in any data-driven organization.

 

Enroll in the Great Learning Academy's Free Supervised Machine Learning Courses today and earn a certificate in data structures to advance your programming skills and career.

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Get started with these courses

BASICS
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

BASICS
Supervised Machine Learning Tutorial
star   4.43 2.4K+ Learners 1 hr

Skills: Supervised Machine Learning, Linear Regression, Characteristics of Supervised Machine Learning

BASICS
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

BASICS
Support Vector Machines
star   4.53 3.2K+ Learners 1 hr

Skills: Introduction to Machine Learning, Kernel Functions, SVM Demo in Python

BASICS
Decision Tree
star   4.43 3.6K+ Learners 1.5 hrs

Skills: Entropy, Heterogeneity, Shannon's Entropy, Preventing Overfitting

BASICS
Random Forest
star   4.37 2.5K+ Learners 1 hr

Skills: Random Forest

BASICS
Logistic Regression on Customer Data
star   4.5 3.2K+ Learners 1 hr

Skills: Logistic Regression on Customer Data

BASICS
Python for Machine Learning
star   4.51 475K+ 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

BASICS
Basics of Machine Learning
star   4.39 149.5K+ Learners 2.5 hrs

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

BASICS
Introduction to Machine Learning
star   4.46 78K+ Learners 1 hr

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.

BASICS
Machine Learning Algorithms
star   4.49 32.5K+ Learners 1.5 hrs

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

BASICS
Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.9K+ Learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

BASICS
Python Libraries for Machine Learning
star   4.55 10.2K+ Learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

BASICS
Supervised Machine Learning with Tree Based Models
star   4.56 9.9K+ Learners 2 hrs

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

BASICS
Data Preparation for Machine Learning
star   4.49 7.5K+ Learners 1 hr

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

New

BASICS
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

BASICS
Supervised Machine Learning Tutorial
star   4.43 2.4K+ Learners 1 hr

Skills: Supervised Machine Learning, Linear Regression, Characteristics of Supervised Machine Learning

BASICS
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

BASICS
Support Vector Machines
star   4.53 3.2K+ Learners 1 hr

Skills: Introduction to Machine Learning, Kernel Functions, SVM Demo in Python

BASICS
Decision Tree
star   4.43 3.6K+ Learners 1.5 hrs

Skills: Entropy, Heterogeneity, Shannon's Entropy, Preventing Overfitting

BASICS
Random Forest
star   4.37 2.5K+ Learners 1 hr

Skills: Random Forest

BASICS
Logistic Regression on Customer Data
star   4.5 3.2K+ Learners 1 hr

Skills: Logistic Regression on Customer Data

Popular

BASICS
Python for Machine Learning
star   4.51 475K+ 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

BASICS
Basics of Machine Learning
star   4.39 149.5K+ Learners 2.5 hrs

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

BASICS
Introduction to Machine Learning
star   4.46 78K+ Learners 1 hr

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.

BASICS
Machine Learning Algorithms
star   4.49 32.5K+ Learners 1.5 hrs

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

BASICS
Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.9K+ Learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

BASICS
Python Libraries for Machine Learning
star   4.55 10.2K+ Learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

BASICS
Supervised Machine Learning with Tree Based Models
star   4.56 9.9K+ Learners 2 hrs

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

BASICS
Data Preparation for Machine Learning
star   4.49 7.5K+ Learners 1 hr

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

Learner reviews of the Free Supervised Machine Learning Courses

Our learners share their experiences of our courses

4.48
67%
24%
6%
1%
2%
Reviewer Profile

5.0

India
“Introduction to Machine Learning: Highly Recommended”
I recently completed the “Introduction to Machine Learning” online course, and I highly recommend it to anyone interested in this fascinating field! The course is exceptionally well-structured, making complex concepts accessible and engaging. The instructor is incredibly knowledgeable and provides clear, concise explanations, ensuring that learners of all levels can follow along. This course is a fantastic starting point for anyone looking to dive into the world of machine learning!
Reviewer Profile

5.0

India
“Engaging Courses, Expert Instructors, Flexible Learning Environment”
I recently completed an online certification course, Introduction to Machine Learning, and I must say, it was an exceptional learning experience. The course content was comprehensive, engaging, and well-structured, making it easy to follow and understand. The instructors were knowledgeable and provided valuable insights throughout the course. I particularly appreciated the quizzes that helped reinforce the concepts learned. The flexibility of the online platform allowed me to study in my own space, which was incredibly convenient. Overall, I am impressed with the quality of the course and the support provided by the Great Learner Academy. Thank you for offering such valuable learning opportunities.
Reviewer Profile

5.0

India
“Transformative Machine Learning Journey with Great Learning: Insights and Progress”
I recently completed a Machine Learning course with Great Learning, and it was an excellent experience. The course content was thorough and well-structured, making complex topics understandable. The instructors were knowledgeable and provided valuable insights, especially with practical applications. I appreciated the hands-on projects, which allowed me to apply what I learned effectively. Overall, the course has significantly improved my understanding of machine learning, and I feel more confident in applying these concepts. I look forward to exploring more courses with Great Learning!
Reviewer Profile

5.0

India
“Excellent Machine Learning Course for Beginners”
This course provides a comprehensive introduction to machine learning. It covers key topics like data preprocessing, model selection, training, and evaluation with a hands-on approach. The lessons are well-structured, making complex concepts easy to understand. The practical exercises and projects are very helpful in reinforcing the material. The instructor is clear and knowledgeable, offering useful insights throughout. This course is ideal for anyone looking to get started in machine learning or enhance their skills in the field.
Reviewer Profile

4.0

India
“The Course Fostered a Sense of Community Among Participants”
I recently completed an online Machine Learning course, and I must say it exceeded my expectations. The course was well-structured, starting with foundational concepts before progressing to more advanced topics. The instructors were knowledgeable and engaging, making complex ideas easier to grasp. The hands-on projects were a highlight, allowing me to apply what I learned in practical scenarios. I particularly appreciated the diverse range of topics covered.
Reviewer Profile

4.0

India
“Mastering Machine Learning: From Fundamentals to Advanced Techniques”
From Fundamentals to Advanced Techniques is a comprehensive learning resource designed for all levels. It begins with foundational concepts like data preprocessing, supervised and unsupervised learning, and essential algorithms. Then, it progresses to advanced topics such as deep learning, natural language processing, and reinforcement learning. You'll gain hands-on experience with popular tools like Python, TensorFlow, and PyTorch, while working on real-world projects across various domains.
Reviewer Profile

5.0

India
“Introduction to Machine Learning: A Transformative Journey”
My learning experience with machine learning was incredible! I enjoyed exploring how algorithms can learn from data to make predictions and decisions. The step-by-step approach, from understanding supervised and unsupervised learning to evaluating models, made the concepts clear and engaging. It was exciting to see real-world applications like recommendation systems and predictive modeling. This introduction provided a solid foundation for deeper exploration in AI and data science.
Reviewer Profile

4.0

India
“Gaining Insight into Machine Learning Fundamentals”
The Introduction to Machine Learning course provided a solid foundation in concepts like supervised and unsupervised learning, data preprocessing, and model evaluation. I appreciated the hands-on projects and clear explanations that made complex topics approachable. It was engaging, insightful, and equipped me with practical skills to explore real-world applications.
Reviewer Profile

5.0

India
“I Really Enjoyed the Machine Learning Course. It Was Fascinating to Dive into the Concepts.”
It was a great experience. The course helped me build confidence in my ability to understand and implement machine learning techniques. I found this course very informative and it helped me gain a solid foundation in machine learning principles.
Reviewer Profile

4.0

India
“Introduction to Machine Learning Course”
An Introduction to Machine Learning course teaches foundational concepts in ML, including supervised, unsupervised, and reinforcement learning. Students learn key algorithms like linear regression, decision trees, and clustering, and how to preprocess data, handle missing values, and evaluate models using metrics like accuracy. The course covers tools such as Python, scikit-learn, and TensorFlow, with hands-on projects to build and evaluate models, while addressing ethical concerns like bias and fairness.

Meet your faculty

Meet industry experts who will teach you relevant skills in Supervised Machine Learning

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

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

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

How can I learn the Supervised Machine Learning course for free?

Great Learning offers free Supervised Machine Learning courses addressing basic to advanced concepts. Enroll in the course that suits your interest through the pool of courses and earn free Supervised Machine Learning certificates of course completion.

Can I learn about Supervised Machine Learning on my own?

With the support of online learning platforms, learning concepts on your own is now possible. Great Learning Academy is a platform that provides free Supervised Machine Learning courses where learners can learn at their own pace.

How long does it take to complete these Supervised Machine Learning courses?

These free Supervised Machine Learning courses offered by Great Learning Academy contain self-paced videos allowing learners to learn crucial concepts and gain in-demand supervised machine learning skills at their convenience.

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

Yes. You will have lifelong access to these free Supervised Machine Learning courses Great Learning Academy offers.

What are my next learning options after these Supervised Machine Learning courses?


You can enroll in Great Learning's highly-appreciated MIT Data Science and Machine Learning Program, which will help you gain advanced ML skills in demand in industries. Complete the course to earn a certificate of course completion.

Is it worth learning Supervised Machine Learning?

Absolutely, it is worth learning Supervised Machine Learning. It is one of the most widely utilized types of machine learning and forms the basis for many real-world applications. Understanding supervised learning provides a solid foundation for other advanced machine learning concepts.
 

Why is Supervised Machine Learning so popular?

Supervised machine learning is popular due to its effectiveness and wide range of applications. It's a machine learning technique that uses labeled data for training a model. Due to its ability to solve real-world problems across a variety of domains, it has gained popularity. Many supervised learning algorithms are both efficient and interpretable, making them easy to implement and understand. This combination of effectiveness, applicability, and accessibility contributes to the popularity of supervised machine learning.

Will I get certificates after completing these free Supervised Machine Learning courses?

You will be awarded free Supervised Machine Learning certificates after completion of your enrolled Supervised Machine Learning free courses.

What knowledge and skills will I gain upon completing these free Supervised Machine Learning courses?

Upon completing these free Supervised Machine Learning courses, you'll gain an in-depth understanding of the core concepts and practical applications of supervised machine learning. This includes implementing and fine-tuning popular algorithms such as Logistic Regression, Naïve Bayes, and various Tree-Based Models.

How much do these Supervised Machine Learning courses cost?

These Supervised Machine Learning courses are provided by Great Learning Academy for free, allowing any learner to learn crucial concepts for free.

Who are eligible to take these free Supervised Machine Learning courses?

Learners, from freshers to working professionals who wish to learn about supervised machine learning and upskill, can enroll in these courses and earn free Supervised Machine Learning certificates of course completion.

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

Choose the free Supervised Machine Learning courses you are looking for and click on the "Enroll Now" button to start your learning experience.

Why take Supervised Machine Learning courses from Great Learning Academy?

Great Learning Academy is the proactive initiative by Great Learning, the leading e-Learning platform, to offer free industry-relevant courses. Free Supervised Machine Learning courses include courses ranging from beginner to advanced level to help learners choose the best fit for them.

What jobs demand you learn Supervised Machine Learning?

 

Here are some job roles that demand knowledge of Supervised Machine Learning:

1. Data Scientist

2. Machine Learning Engineer

3. AI Engineer

4. Data Analyst

5. Business Intelligence Analyst

6. Risk Analyst

7. Bioinformatics Specialist

8. Quantitative Analyst

9. Computer Vision Engineer

10. NLP Scientist