Machine learning is a rapidly growing field within artificial intelligence that allows computers to analyze large data sets, identify patterns, predict future outcomes, and make informed decisions. It has become a highly sought-after skill in the job market and is being applied in a wide range of industries, from finance to robotics.
Machine learning algorithms work by learning from past experiences and using that knowledge to understand new information and make predictions based on it. This technology is already being utilized in many apps, websites, and other services that we use daily, and its potential for future growth is vast.
As machine learning continues to be a hot topic in the tech industry, more and more people are looking to learn about this exciting field. One platform that offers a wide variety of machine learning courses is Udemy. With its diverse selection of courses, Udemy is a great resource for anyone looking to improve their skills in this area.
However, with so many courses to choose from, it can be overwhelming to figure out which ones are the best fit for your needs. That's why we've compiled a list of the top machine learning courses on Udemy. These courses have received high ratings and positive reviews from students, and cover a range of topics to help you get started in machine learning and these courses will also provide you with the skills and knowledge to understand and implement machine learning concepts and build your own AI applications or experiment with new ideas.
1. Machine Learning A-Z™: Hands-On Python & R In Data Science
Machine Learning A-Z™ is a comprehensive introduction to the fundamentals of machine learning, with a focus on practical, hands-on application using computer science tools. This course is designed for individuals who are new to machine learning and data science and want to learn the key concepts and techniques. It covers the basics of machine learning, including the use of Python and R, two of the most widely used programming languages in this field. The course is taught by two experienced instructors and has been popular among over 754,000 students on the Udemy platform. It is suitable for individuals with some programming experience, but no prior knowledge of machine learning is required.
Course Rating - 4.5 / 5
Course Instructors - Kirill Eremenko (Data Scientist) and Hadelin de Ponteves (AI Entrepreneur)
Price - $129.99 $12.99 Get 90% Off Now!
2. Python for Data Science and Machine Learning Bootcamp
Python for Data Science and Machine Learning Bootcamp is a course that aims to provide a comprehensive introduction to machine learning and data science using the Python programming language. Throughout the course, you will learn the principles of machine learning and gain practical experience using Python to solve real-world problems. You will also be introduced to key machine learning and data science algorithms, and learn how to use them effectively. The course covers a wide range of topics, including Spark for big data analysis, NumPy for numerical data, Pandas for data analysis, Matplotlib and Seaborn for plotting, Plotly for interactive visualizations, SciKit-Learn for machine learning tasks, and more. You will also learn about K-Means clustering, logistic regression, linear regression, random forest and decision trees, natural language processing, spam filters, neural networks, and support vector machines. By the end of the course, you will have a strong foundation in machine learning and data science using Python.
Course Rating - 4.6 / 5
Course Instructors - Jose Portilla (Head of Data Science, Pierian Data Inc.)
Price - $129.99 $12.99 Get 90% Off Now!
3. Machine Learning, Data Science and Deep Learning with Python
This is a comprehensive course designed to provide a hands-on guide to mastering machine learning, data science, and deep learning. It has been taken by over 144,000 students and covers a wide range of topics, including linear and polynomial regression, artificial neural networks, image and data classification, data visualization, and reinforcement learning. The course also includes a practical project where you can build a Pac-Man bot using reinforcement learning. In order to successfully complete this course, you will need some programming experience with Python and a basic understanding of high school math. By the end of the course, you will have a solid foundation in machine learning, data science, and deep learning using Python.
Course Rating - 4.6 / 5
Course Instructors - Frank Kane (Founder, Sundog Education)
Price - $129.99 $12.99 Get 90% Off Now!
4. Data Science and Machine Learning Bootcamp with R
The Data Science and Machine Learning Bootcamp with R is a comprehensive course that teaches you the fundamentals of data science and machine learning using the R programming language. It is designed to be highly interactive, with a focus on hands-on learning and practical application. The course begins by teaching you the basics of R programming, and then progresses to more advanced topics such as working with large data sets and making predictions based on that data. Whether you are new to R or have some experience with it, this course is suitable for you. It is a great resource for anyone looking to learn more about data science and machine learning, or to gain the skills and knowledge needed to work with data in a professional setting. If you are interested in working with data or simply understanding it better, this course is an excellent choice.
Course Rating - 4.6 / 5
Course Instructors - Jose Portilla (Head of Data Science, Pierian Data Inc.)
Price - $129.99 $12.99 Get 90% Off Now!
5. Scala and Spark for Big Data and Machine Learning
Scala and Spark are powerful technologies that are increasingly being used in the field of big data and machine learning. Scala is a programming language that is well-suited for large-scale data processing tasks, and Spark is a powerful tool that allows you to perform distributed data processing on large datasets. Together, Scala and Spark form a powerful combination that is widely used by data scientists and engineers.
If you're interested in learning how to use these technologies together for large-scale data processing, this course is a great place to start. It begins with an introduction to Scala programming and then gradually introduces you to using Spark for processing large datasets. By the end of the course, you will have a strong understanding of how to use Scala and Spark together for efficient data processing.
With a rating of 4.6 out of 5, this course has received high praise from previous students and is a great choice for anyone looking to learn how to use Scala and Spark for large-scale data processing.
Course Rating - 4.6 / 5
Course Instructors - Jose Portilla (Head of Data Science, Pierian Data Inc.)
Price - $129.99 $12.99 Get 90% Off Now!
6. Machine Learning Practicals: 6 Real-World Applications
The "Machine Learning Practicals: 6 Real-World Applications" course is designed to give you hands-on experience solving real industry machine learning problems using Python. Through this course, you will gain a better understanding of what a real data science project looks like and be able to include these case studies in your resume to market yourself as a machine learning practitioner. Additionally, you will feel more confident during data science interviews and learn how to chain multiple machine learning algorithms together to achieve a goal.
In addition to learning practical skills, you will also learn advanced data visualization techniques using Seaborn and Matplotlib and become proficient in machine learning algorithms such as logistic regression and random forest classifier. You will also learn about L1 regularization (also known as Lasso), which is a technique used to prevent overfitting in machine learning models.
Overall, this course is designed to give you the skills and knowledge you need to succeed as a machine learning practitioner and feel confident tackling real-world industry problems.
Course Rating - 4.3 / 5
Course Instructors - Rony Sulca (Data Scientist at MoneyLion)
Price - $129.99 $12.99 Get 90% Off Now!
7. Unsupervised Machine Learning Hidden Markov Models in Python
In unsupervised machine learning, we do not have access to labeled training data, so we need to find other ways to train our models. One such method is through the use of hidden Markov models (HMMs), which can allow us to classify observations without any labels.
In this course, you will learn how to implement a hidden Markov model in Python from scratch and use it to classify sequences of observations. Some of the topics you will cover include:
- The basics of HMMs and their applications in unsupervised machine learning
- How to implement an HMM in Python, including the forward and backward algorithms
- Techniques for estimating the parameters of an HMM using the Baum-Welch algorithm
- How to use HMMs to classify sequences of observations and make predictions
By the end of this course, you will have a solid understanding of how to use hidden Markov models for unsupervised machine learning and be able to apply these techniques to real-world problems.
Course Rating - 4.7 / 5
Course Instructors - Lazy Programmer Team (Artificial Intelligence and Machine Learning Engineer)
Price - $129.99 $12.99 Get 90% Off Now!
Machine Learning is one of the hot fields with the big money right now. And for good reason: it’s the engine powering the next wave of intelligent applications and services. Overall, these courses are a great way to get started with machine learning and build the skills you need to succeed in this exciting field. Whether you're a beginner or an experienced programmer, there's a course on this list that's right for you. So if you're interested in learning more about machine learning, be sure to check out these top courses on Udemy.
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