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Free Machine Learning Courses
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Great Learning Academy
Machine Learning Essentials with Python
Skills: Introduction to Machine Learning, Supervised Learning - Linear Regression, Supervised Learning - Logistic Regression, Ensemble Techniques, Unsupervised Learning, PCA, Feature Engineering and Cross Validation, Models and Hyperparameter Tuning

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Machine Learning Essentials with Python
What you’ll learn:
- Introduction to Machine Learning
- Supervised Learning - Linear Regression
- Supervised Learning - Logistic Regression
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Free Machine Learning Courses


Great Learning Academy
Data Preparation for Machine Learning
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Data Preparation for Machine Learning
What you’ll learn:
- Case Study
- Agenda For Preparing Data For Machine Learning
- Data Leakage
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Great Learning Academy

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Python for Machine Learning
What you’ll learn:
- Intro to Numpy
- Joining NumPy Arrays
- Numpy Intersection & Difference
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Great Learning Academy
Python Libraries for Machine Learning
Skills: Numpy, Pandas, Matplotlib, SeaBorn

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Python Libraries for Machine Learning
What you’ll learn:
- NumPy
- Pandas
- Matplotlib
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Great Learning Academy
NumPy Tutorial
Skills: Numpy Scalar Functions,Numpy Mathematical Operations,Numpy Arrays,Numpy joining, intersection, and difference,Numpy Matrix Calculations

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NumPy Tutorial
What you’ll learn:
- Introduction to NumPy
- NumPy Operations
- NumPy Mathematics
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Great Learning Academy
Python Pandas
Skills: Introduction to Pandas and DataFrames, Understanding the Usage of DataFrames, Various DataFrame methods and Operations, Selecting and Indexing Operations, Pandas Aggregation Operations

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Python Pandas
What you’ll learn:
- Introduction to Pandas and DataFrames
- Working with the Pandas Series Data Structure
- Understanding the usage of DataFrames
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Great Learning Academy
Uses of Pandas
Skills: Pandas , Uses of Pandas, Functions in Pandas

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Uses of Pandas
What you’ll learn:
- Data visualization
- Pre-Requistes
- Top 5 uses of Pandas
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Great Learning Academy
Introduction to Scikit Learn
Skills: Scikit learn, Installing Scikit learn

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Introduction to Scikit Learn
What you’ll learn:
- Practical Demo in Python
- What is Scikit learn?
- Installing Scikit learn
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Great Learning Academy
SciPy in Python
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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SciPy in Python
What you’ll learn:
- Summary
- SciPy in Python Course Agenda
- Introduction to SciPy
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Great Learning Academy
Data Visualization using Python
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Data Visualization using Python
What you’ll learn:
- Packages for Data Visualization in Python
- Comparing different Plots in Python
- Working and Visualising different datasets in Python
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Great Learning Academy
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Great Learning Academy
Skills: NumPy, Pandas

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Great Learning Academy
Skills: Numpy, Pandas, Matplotlib, SeaBorn

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

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Great Learning Academy
Skills: Introduction to Pandas and DataFrames, Understanding the Usage of DataFrames, Various DataFrame methods and Operations, Selecting and Indexing Operations, Pandas Aggregation Operations

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Great Learning Academy
Skills: Pandas , Uses of Pandas, Functions in Pandas

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Great Learning Academy
Skills: Scikit learn, Installing Scikit learn

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Great Learning Academy
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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Great Learning Academy
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Great Learning Academy

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Python for Machine Learning
What you’ll learn:
- Intro to Numpy
- Joining NumPy Arrays
- Numpy Intersection & Difference
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Great Learning Academy
Basics of Machine Learning
Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

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Basics of Machine Learning
What you’ll learn:
- Introduction to Machine Learning and Linear Regression
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Great Learning Academy
Data Visualization using Python
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Data Visualization using Python
What you’ll learn:
- Packages for Data Visualization in Python
- Comparing different Plots in Python
- Working and Visualising different datasets in Python
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Great Learning Academy
Python Project Development
Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data

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Python Project Development
What you’ll learn:
- Word Counter using Python
- Word Game using Python
- Calculator with Python
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Great Learning Academy
Application of Classification Algorithms
Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree

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Application of Classification Algorithms
What you’ll learn:
- Naive Bayes
- Logistic Regression
- Decision Tree
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Great Learning Academy

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Machine Learning Landscape
What you’ll learn:
- What Machine Learning?
- Introduction to the Course
- Why do we need ML?
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Great Learning Academy
Bagging and Boosting
Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python

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Bagging and Boosting
What you’ll learn:
- Working with Prediction Errors
- Understanding Ensemble Methods
- Introduction to Bagging
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Great Learning Academy
Machine Learning Modelling
Skills: Linear Regression, Logistic Regression, Naïve Bayes

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Machine Learning Modelling
What you’ll learn:
- What is Naïve Bayes?
- Introduction to Linear Regression
- Linear Regression Modelling
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Great Learning Academy
Predictive Analytics for Machine Learning
Skills: Predictive Analytics, Feature Engineering, Deep Feature Synthesis, Model Selection Techniques

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Predictive Analytics for Machine Learning
What you’ll learn:
- Introduction to Predictive Analytics and Feature Engineering
- Prediction Engineering Introduction
- Feature Egineering Introduction
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Great Learning Academy
Feature Engineering for Machine Learning
Skills: Introduction to Feature Engineering, Under sampling, Over sampling

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Feature Engineering for Machine Learning
What you’ll learn:
- Introduction to Feature Engineering
- Concept of Undersampling and Oversampling
- Hands-on exercise showing tuning of model
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Great Learning Academy
Data Preparation for Machine Learning
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Data Preparation for Machine Learning
What you’ll learn:
- Case Study
- Agenda For Preparing Data For Machine Learning
- Data Leakage
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Great Learning Academy
Predicting Fleet Failure in Car Rental Company
Skills: Prediction Modeling Techniques, Exploratory Data Analysis

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Predicting Fleet Failure in Car Rental Company
What you’ll learn:
- Data Science Lifecycle
- Case Study
- Introduction To Predictive Maintenance For Car Rentals
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Popular


Great Learning Academy

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Python for Machine Learning
What you’ll learn:
- Intro to Numpy
- Joining NumPy Arrays
- Numpy Intersection & Difference
View Course
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Great Learning Academy
Basics of Machine Learning
Skills: Introduction to Machine Learning, Supervised Machine Learning, Linear Regression, Pearson's Coefficient, Coefficient of Determinant

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Basics of Machine Learning
What you’ll learn:
- Introduction to Machine Learning and Linear Regression
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Great Learning Academy
Data Visualization using Python
Skills: Python Basics, NumPy, Pandas, Matplotlib, Seaborn, Plotly

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Data Visualization using Python
What you’ll learn:
- Packages for Data Visualization in Python
- Comparing different Plots in Python
- Working and Visualising different datasets in Python
View Course


Great Learning Academy
Python Project Development
Skills: Covid Analysis, Analysis of Indian Education System, Project on FIFA Data

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Python Project Development
What you’ll learn:
- Word Counter using Python
- Word Game using Python
- Calculator with Python
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Trending


Great Learning Academy
Application of Classification Algorithms
Skills: Supervised Learning, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Naive Bayes, Decision Tree

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Application of Classification Algorithms
What you’ll learn:
- Naive Bayes
- Logistic Regression
- Decision Tree
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Great Learning Academy

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Machine Learning Landscape
What you’ll learn:
- What Machine Learning?
- Introduction to the Course
- Why do we need ML?
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Great Learning Academy
Bagging and Boosting
Skills: Working with Prediction Errors, Understanding Ensemble Methods, Introduction to Bagging and Boosting, Bagging vs Boosting, Practical Demo in Python

View Course
Bagging and Boosting
What you’ll learn:
- Working with Prediction Errors
- Understanding Ensemble Methods
- Introduction to Bagging
View Course


Great Learning Academy
Machine Learning Modelling
Skills: Linear Regression, Logistic Regression, Naïve Bayes

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Machine Learning Modelling
What you’ll learn:
- What is Naïve Bayes?
- Introduction to Linear Regression
- Linear Regression Modelling
View Course
New


Great Learning Academy
Predictive Analytics for Machine Learning
Skills: Predictive Analytics, Feature Engineering, Deep Feature Synthesis, Model Selection Techniques

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Predictive Analytics for Machine Learning
What you’ll learn:
- Introduction to Predictive Analytics and Feature Engineering
- Prediction Engineering Introduction
- Feature Egineering Introduction
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Great Learning Academy
Feature Engineering for Machine Learning
Skills: Introduction to Feature Engineering, Under sampling, Over sampling

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Feature Engineering for Machine Learning
What you’ll learn:
- Introduction to Feature Engineering
- Concept of Undersampling and Oversampling
- Hands-on exercise showing tuning of model
View Course


Great Learning Academy
Data Preparation for Machine Learning
Skills: Data Leakage, Data Balancing, K-fold Cross Validation, Model Building

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Data Preparation for Machine Learning
What you’ll learn:
- Case Study
- Agenda For Preparing Data For Machine Learning
- Data Leakage
View Course


Great Learning Academy
Predicting Fleet Failure in Car Rental Company
Skills: Prediction Modeling Techniques, Exploratory Data Analysis

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Predicting Fleet Failure in Car Rental Company
What you’ll learn:
- Data Science Lifecycle
- Case Study
- Introduction To Predictive Maintenance For Car Rentals
View Course
Learner reviews of the Free Machine Learning Courses
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Empowering millions through professional learning
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Learn Machine Learning & Get Completion Certificates
Machine Learning is a subdomain of artificial intelligence that enables computers to learn from huge data sets, identify patterns, and make logical decisions with minimal human intervention. This technology is used to optimize various tasks, such as predicting customer behavior, optimizing supply chains, and recognizing objects in images.
At its core, machine learning is about using algorithms to identify patterns in data. These algorithms can be used to make predictions and recommendations based on the data that has been collected. For example, a machine learning algorithm can predict whether a customer will make a purchase based on their past purchase history.
Machine learning can be used in various applications, including computer vision, natural language processing, and neural networks. In computer vision, machine learning algorithms can recognize objects in images or videos. These algorithms can interpret and translate spoken language in natural language processing. Neural networks create computer systems that can think and learn like humans.
Machine learning is an ever-evolving field that is becoming increasingly important in today's world. This technology can revolutionize how businesses function and how people interact with technology. As machine learning becomes more advanced, it will open up new possibilities in various industries.
1.Applications of Machine Learning
Machine learning is a powerful technology that can be applied to various applications. From analyzing text and images to predicting customer behavior, machine learning algorithms can be used to make data-driven decisions. Here are some of the most common applications of machine learning.
2.Image Recognition: Machine learning algorithms can identify objects, faces, and other image features. This technology is widely used in facial recognition systems, medical imaging, and self-driving cars.
3.Recommender Systems:Recommender systems use machine learning algorithms to suggest items to users based on their preferences. This technology is widely used by online retailers, streaming services, and social media platforms.
4.Speech Recognition: Speech recognition technology uses machine learning algorithms to understand spoken language. It is used in many applications, including voice-activated assistants, customer service systems, and automated call centers.
5.Predictive Analytics: Predictive analytics method uses machine learning algorithms to make predictions. It can anticipate customer behavior, detect fraud, and predict stock prices.
6. Robotics: Robotics is a field that relies heavily on machine learning algorithms. Robots can be programmed to use machine learning algorithms to recognize objects, navigate their environment, and interact with humans.
Organizations can gain valuable insights and make data-driven decisions by utilizing the power of machine learning algorithms. With suitable applications, machine learning can open up a world of business possibilities.
Great Learning offers free Machine Learning courses to help you gain proficiency in this domain. Experts teach our courses and provide learners with the necessary knowledge and skills. The courses are comprehensive and cover all the topics related to Machine Learning, from introductory concepts to advanced topics. By the end of these courses, you will have the necessary proficiency to work with Machine Learning applications. The best part about these courses is that they are free and offer certificates of completion to all learners. The certificates are proof of your proficiency in Machine Learning and can help open up a variety of career prospects for you.
Great Learning also provides an AI and Machine Learning course to help learners throughout the learning process. You can get all the help you need, from downloadable study materials to practice tests. So, start your Machine Learning course today if you want to learn Machine Learning. With our courses, you can gain proficiency in this domain and get a certificate to prove it.
Meet your faculty
Meet industry experts who will teach you relevant skills in artificial intelligence

Mr. Bharani Akella

Mr. Bharani Akella

Dr. Abhinanda Sarkar
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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. Abhinanda Sarkar
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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

Prof. Mukesh Rao
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20+ years of expertise in AI, machine learning, and analytics
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Director - Academics at Great Learning
Frequently Asked Questions
What are the prerequisites required to learn these free Machine Learning courses?
There's no prior experience necessary to begin, but before you learn advanced courses, complete introductory courses to have solid foundations and develop an interest in working on machine learning algorithms and technologies.
How long does it take to complete these Machine Learning free courses?
These courses include 1-8 hours of comprehensive video lectures. These courses are, however, self-paced, and you can complete them at your convenience.
What knowledge and skills will I gain upon completing these free Machine Learning courses?
By completing free Machine Learning courses, you will gain a comprehensive knowledge of the fundamentals of Machine Learning, along with a range of practical skills that you can use to apply Machine Learning techniques in various applications. You will learn the principles behind supervised and unsupervised learning, and you will be able to identify the appropriate algorithms for different tasks. You will also be able to develop and evaluate predictive models and apply them to real-world problems. Furthermore, you will learn how to manipulate and visualize data with a range of tools and techniques and gain an understanding of the ethical implications of using Machine Learning.
Do I get any certification from these Machine Learning courses?
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.
Will I get a certificate after completing these free Machine Learning courses?
Yes. After completing them successfully, you will receive a certificate of completion for each course.
How much do these Machine Learning courses cost?
These are free courses; you can enroll and learn for free online.
What are my next learning options after these Machine Learning courses?
These free Machine Learning courses give you a competitive edge in your professional life. Register for the AI and Machine Learning courses to further gain professional knowledge after completing these free courses.
Is it worth learning about Machine Learning?
Yes, learning about Machine Learning is definitely worth your time and effort! Machine Learning is a rapidly growing technology revolutionizing how businesses and organizations operate. It has many applications, including data mining, natural language processing, and computer vision. As technology continues to advance, it will become increasingly important for individuals and organizations to understand the basics of machine learning and to be able to apply it to their projects. The potential of machine learning is vast and can lead to new and exciting opportunities for those willing to explore and take the time to learn about it.
Why is Machine Learning so popular?
Machine Learning has become increasingly popular due to its ability to make predictions and decisions from large amounts of data with little or no human intervention. Machine Learning algorithms can learn from data and improve over time, making them increasingly useful for various tasks such as recognizing patterns in images, predicting customer behavior, and recognizing speech. As data sets become more complex, Machine Learning offers an efficient and powerful way to make sense of the data and make decisions based on it. Additionally, the cost of computing has decreased significantly in recent years, making Machine Learning more accessible and cost-effective.
What jobs demand you learn Machine Learning?
Jobs that are directly related to Machine Learning are,
- Data Scientists
- Machine Learning Engineers
- Software Engineers
- Robotics Engineers
- Computer Vision Engineers
- Artificial Intelligence Engineers
- Research Scientists.
Additionally, more and more jobs are being created requiring machine learning knowledge, such as Big Data Engineers and Deep Learning Engineers.
Why take Machine Learning 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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