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Free Supervised Machine Learning Courses

img icon BASICS
Introduction to Machine Learning
star   4.46 76.6K+ learners 1 hr

Skills: Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Linear Regression, Classification, Recommender System, Kaggle, Hackathon, ML on Cloud, Data Science, Model Training, Machine Learning Platforms, Data-Driven Intelligence

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Data Preparation for Machine Learning
star   4.49 7K+ learners 1 hr

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

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Python for Machine Learning
star   4.51 467.4K+ 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 9.9K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

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Basics of Machine Learning
star   4.39 146.4K+ learners 2.5 hrs

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

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Machine Learning Algorithms
star   4.49 31.9K+ 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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Supervised Machine Learning Tutorial
star   4.43 2.2K+ learners 1 hr

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

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Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.7K+ learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

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Logistic Regression on Customer Data
star   4.53 3.2K+ learners 1 hr

Skills: Logistic Regression on Customer Data

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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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Decision Tree
star   4.43 3.6K+ learners 1.5 hrs

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

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Support Vector Machines
star   4.53 3.2K+ learners 1 hr

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

img icon BASICS
Introduction to Machine Learning
star   4.46 76.6K+ learners 1 hr

Skills: Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Linear Regression, Classification, Recommender System, Kaggle, Hackathon, ML on Cloud, Data Science, Model Training, Machine Learning Platforms, Data-Driven Intelligence

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Data Preparation for Machine Learning
star   4.49 7K+ learners 1 hr

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

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Python for Machine Learning
star   4.51 467.4K+ 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
Python Libraries for Machine Learning
star   4.55 9.9K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

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Basics of Machine Learning
star   4.39 146.4K+ learners 2.5 hrs

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

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Machine Learning Algorithms
star   4.49 31.9K+ 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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Supervised Machine Learning Tutorial
star   4.43 2.2K+ learners 1 hr

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

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Supervised Machine Learning with Logistic Regression and Naïve Bayes

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

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Logistic Regression on Customer Data
star   4.53 3.2K+ learners 1 hr

Skills: Logistic Regression on Customer Data

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Supervised Machine Learning with Tree Based Models

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

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Decision Tree
star   4.43 3.6K+ learners 1.5 hrs

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

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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

img icon 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

img icon BASICS
Supervised Machine Learning Tutorial
star   4.43 2.2K+ learners 1 hr

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

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KNN Algorithm
star   4.41 3K+ learners 0.5 hr

Skills: KNN, KNN Demo

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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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Support Vector Machines
star   4.53 3.2K+ learners 1 hr

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

img icon BASICS
Decision Tree
star   4.43 3.6K+ learners 1.5 hrs

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

img icon BASICS
Random Forest
star   4.36 2.5K+ learners 1 hr

Skills: Random Forest

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Logistic Regression on Customer Data
star   4.53 3.2K+ learners 1 hr

Skills: Logistic Regression on Customer Data

img icon BASICS
Python for Machine Learning
star   4.51 467.4K+ 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   4.39 146.4K+ learners 2.5 hrs

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

img icon BASICS
Introduction to Machine Learning
star   4.46 76.6K+ learners 1 hr

Skills: Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Linear Regression, Classification, Recommender System, Kaggle, Hackathon, ML on Cloud, Data Science, Model Training, Machine Learning Platforms, Data-Driven Intelligence

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Machine Learning Algorithms
star   4.49 31.9K+ 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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Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.7K+ learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

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Python Libraries for Machine Learning
star   4.55 9.9K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

img icon BASICS
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

img icon BASICS
Data Preparation for Machine Learning
star   4.49 7K+ learners 1 hr

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

New

img icon 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

img icon BASICS
Supervised Machine Learning Tutorial
star   4.43 2.2K+ learners 1 hr

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

img icon BASICS
KNN Algorithm
star   4.41 3K+ learners 0.5 hr

Skills: KNN, KNN Demo

img icon 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

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Support Vector Machines
star   4.53 3.2K+ learners 1 hr

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

img icon BASICS
Decision Tree
star   4.43 3.6K+ learners 1.5 hrs

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

img icon BASICS
Random Forest
star   4.36 2.5K+ learners 1 hr

Skills: Random Forest

img icon BASICS
Logistic Regression on Customer Data
star   4.53 3.2K+ learners 1 hr

Skills: Logistic Regression on Customer Data

Popular

img icon BASICS
Python for Machine Learning
star   4.51 467.4K+ 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   4.39 146.4K+ learners 2.5 hrs

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

img icon BASICS
Introduction to Machine Learning
star   4.46 76.6K+ learners 1 hr

Skills: Introduction to Machine Learning, Supervised Learning, Unsupervised Learning, Linear Regression, Classification, Recommender System, Kaggle, Hackathon, ML on Cloud, Data Science, Model Training, Machine Learning Platforms, Data-Driven Intelligence

img icon BASICS
Machine Learning Algorithms
star   4.49 31.9K+ learners 1.5 hrs

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

img icon BASICS
Supervised Machine Learning with Logistic Regression and Naïve Bayes
star   4.43 21.7K+ learners 2 hrs

Skills: Scikit Learn Library,Logistic Regression, Naïve Bayes

img icon BASICS
Python Libraries for Machine Learning
star   4.55 9.9K+ learners 2.5 hrs

Skills: Numpy, Pandas, Matplotlib, SeaBorn

img icon BASICS
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

img icon BASICS
Data Preparation for Machine Learning
star   4.49 7K+ 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%
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Reviewer Profile

5.0

Country Flag India
“Mastering Machine Learning for Beginners”
This course provides a solid foundation in Machine Learning, covering key concepts like supervised and unsupervised learning, recommendation systems, and practical applications. It simplifies complex topics with clear examples and quizzes, making it ideal for beginners. A hands-on approach ensures learners can apply knowledge effectively in real-world scenarios.

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Reviewer Profile

5.0

Country Flag India
“Insightful and Practical Learning Journey”
I really enjoyed the structure of the course and the way complex topics like machine learning were broken down into simple, understandable lessons. The interactive quizzes reinforced my understanding, and the practical approach kept me engaged throughout. This course gave me both foundational knowledge and practical insights, preparing me well for real-world applications. I highly recommend it to anyone looking to get started with machine learning!

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Reviewer Profile

5.0

Country Flag India
“The Teacher Was Very Knowledgeable, Engaging, and Supportive”
The teacher was very knowledgeable, engaging, and supportive, making the learning experience both enjoyable and informative.

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Reviewer Profile

5.0

Country Flag Indonesia
“Understand Advanced Concepts with Real Examples”
This assignment really helped me understand the basic and advanced concepts of the topics studied. The explanations are clear, and the examples are relevant to real-world situations, making the material easier to digest. I feel more confident to apply this knowledge in future projects. Highly recommended for those who want to deepen their understanding.

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Reviewer Profile

5.0

“Amazing Teacher - Great Teaching Style”
I really loved how simple he made it all sound. I have no previous experience in machine learning, and the teacher's choice of words and teaching method is really amazing.

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Reviewer Profile

5.0

Country Flag India
“Thrill of Solving Complex Problems with ML Algorithms”
What I enjoyed most about the ML course was diving into the hands-on projects, where theory met practice. Solving real-world problems with powerful algorithms and uncovering hidden patterns in data was incredibly satisfying and eye-opening. It truly highlighted the transformative power of machine learning.

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Reviewer Profile

5.0

Country Flag India
“Introduction to Machine Learning by Great Learning”
The online free course was well-structured and provided valuable insights into the subject matter. The content was clear, relevant, and easy to understand, with practical examples that enhanced the learning experience. The accessibility of the materials, including videos and quizzes, made it convenient to follow along at my own pace. The instructor was knowledgeable and explained concepts effectively, ensuring a good grasp of the topics. Overall, it was an excellent learning opportunity, and I appreciate the effort put into making quality education available for free.

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Reviewer Profile

5.0

Country Flag India
“Great Learning on 'Introduction to Machine Learning'”
It was really very good, with clear explanations about supervised and unsupervised learning, the Netflix prize, and ML on the cloud.

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Reviewer Profile

5.0

“Comprehensive and Engaging Learning Experience”
Great Learning offers a comprehensive and engaging learning experience. The well-structured courses, expert instructors, and interactive learning materials make complex topics accessible. The platform's flexibility allows for self-paced learning, while the supportive community fosters collaboration and knowledge sharing. The hands-on projects and real-world case studies enhance practical application. Overall, Great Learning provides a valuable opportunity for professional development and skill enhancement.

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Reviewer Profile

5.0

Country Flag Nigeria
“Highlight of Your Learning Experience”
I loved how the course combined videos, quizzes, and hands-on activities to keep things interesting and cater to different learning styles. It was a comprehensive experience that not only increased my knowledge but also built my confidence in applying these skills.

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Meet your faculty

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

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.
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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.
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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