Top 10 Best Data Science Courses Online in 2023

The demand for professional data science experts in government, industry, and academia is accelerating. To attain the necessary knowledge and high-end skills required for tackling real-world challenges, individuals can enroll in some of the best data science courses.

These specialized courses offer a solid grounding in the basics of data science, which can go a long way in helping you develop a career. Here we list the best data science courses. First, we offer a summarized list, before we describe the courses in detail.

Best Data Science Courses

Is it Worth Learning Machine Learning in 2023?

Machine learning is one of the hottest trends in the software industry. In about ten years, there has been a 650% growth in machine learning related jobs. This will only increase as the field finds more applications in various industries. The field is absolutely worth learning, and can be used in tandem with other fields to create industry-specific products.

Best Data Science Courses

In choosing the best online data science programs, we focused on depth of coverage, cost, practical projects, and general quality. This list is by no means exhaustive, but it offers a fairly comprehensive range of choices.

1. Machine Learning, Data Science, and Deep Learning with Python - Hackr Recommended

This Udemy machine learning course covers all the major topics related to machine learning, including artificial neural networks, K-means clustering, and support vector machines. Additionally, you'll learn the technicalities of data visualization with Seaborn and MatPlotLib, and the practical implementation of machine learning on a large scale with MLLib Apache Spark.

The course also ventures into deep learning, teaching you how to classify sentiments, images, and data using deep learning concepts. It is an ideal learning program for professional programmers and data analysts intending to switch their careers. You can opt for this specialization even if you are new to Python as it features a crash course for a better understanding of the language.

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2. MicroMasters Program in Statistics and Data Science

MIT’s MicroMasters Program in Statistics and Data Science program features a five-course series formulated to strengthen their foundation in machine learning, data science, and statistics. It is an ideal course for students who wish to learn big data analysis. You’ll also acquire a good understanding of making data-driven predictions using probabilistic modeling, statistical inference, and unsupervised learning techniques and supervised techniques. 

With this course, you can dive deeper into the concepts of statistics, data analysis techniques, probability, machine learning algorithms, and more. On completing this specialization, students will be compatible for the roles of system analyst, data analyst, and data scientist, among others.

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3. Data Science Specialization Course

John Hopkins’ data science specialization course covers all the tools and concepts for a career in data science. They start by asking the right questions to draw inferences and then publishing the achieved results. The final capstone project focuses on the skills required to use real-world data to build a data product. 

This course includes two components, including learning how to turn data into actionable knowledge. You will get an overview of the tools, questions, and data that data scientists and data analysts require to work. 

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4. Machine Learning with Javascript

Designed for the Javascript developers, this machine learning course dives into advanced memory profiling, building Tensorflow JS library-powered apps, writing ML code, and other major topics relevant for a thorough understanding of the subject.

Additionally, you'll also learn to create programs compatible with both Node JS and the browser. The course will explain performance-enhancing techniques and strategies specifically for Javascript.

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5. The Complete Machine Learning Course with Python

The complete machine learning course with Python teaches you how to differentiate between machine learning and classical programming, machine learning, and deep learning. You'll also acquire knowledge about neural networks, tensor operations, and advanced topics such as validation, dropout, testing, regularization, and under and overfitting.

You'll acquire a good understanding of machine learning tools used for tackling real-world issues. It's a great course to learn about ML performance metrics, including recall, R-squared, confusion matrix, MSE, prevision, and accuracy.

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6. Data Science: Machine Learning

Offered by Harvard University, this data science specialization is created to help aspirants learn machine learning and the technical problems associated with it. Unlike other courses, this learning program will help you dig deeper into ML's data science methodologies.

The program also offers knowledge of training data and efficient ways of using data sets for discovering predictive relationships. During the course, you'll learn about implementing machine learning in various products such as speech recognition, postal service, and spam detectors, among other things.

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7. Intro to Machine Learning with PyTorch

Available at Udacity, this intro to machine learning program focuses particularly on supervised models, data cleaning, machine learning algorithms, unsupervised learning, and deep learning. The online course is divided into different steps, with each one offering practical assignments to learners that include code projects and exercises.

The specialization offers an immersive learning experience through the creation of products that top-tier organizations might use. Students are also offered guidance for such things as interview preparation, professional profile maintenance, and other crucial aspects of career growth.

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8. HarvardX's Data Science Professional Certificate

The HarvardX data science program teaches students the essential skills and knowledge for handling real-world challenges related to data analysis. The specialization covers core concepts such as inference, machine learning, and regression. You'll also learn to develop basic skill sets, including data visualization using ggplot2, R programming, data wrangling using dplyr, Linux, and file organization.

Additionally, you'll also learn the tricks and techniques of implementing machine learning algorithms using advanced tools. The program also offers a deeper dive into data science concepts through business case studies.

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9. Introduction to Machine Learning Course

This machine-learning program on Udemy covers both statistics and computer science. The well-rounded course also dives into the more technical aspects of machine learning, such as algorithms and support vector machines. 

In addition, you'll also learn how to extract and identify useful machine learning features for the best representation of data. The course offers a rich learning experience thanks to its professionally designed syllabus. 

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10. ColumbiaX's Artificial Intelligence MicroMasters Program

This edX AI and machine learning course cover all the core topics of the field and additional topics like robotics and CGI motion. You'll also gain hands-on experience in applying the concepts through real-life examples.

It is an ideal course for students pursuing computer science graduate courses who want some additional knowledge to go with the degree. The specialization teaches students about developing automated computer systems in bioinformatics, robotic control, autonomous navigation, data mining, and other advanced systems.

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Conclusion

Machine learning is an interesting subject with immense application potential. It allows practitioners to boundlessly experiment with their skills and knowledge. To build a career in this field, you should prioritize gaining a good grounding in a few key concepts and how to apply them. 

Pick any of the programs in our best online data science courses to list to start your journey. These are worth the time and money, and allow you to learn anywhere and at any time.

Frequently Asked Questions

1. Are Data Science certificates worth it? 

Data science certificates can be beneficial because they prove that you have the skill and knowledge to work on related projects. A certification from a reputed academic institution can be the difference when applying for a position.

2. What should a data science course syllabus include? 

There are several important subjects that should be included in the syllabus of a data science course. These include algorithms, functions, and tools. The top data science courses cover everything you need to know about machine learning.

3. How do I prepare for a data science course? 

You can prepare for a data science course by studying theory and actually working on projects. There are plenty of datasets available on the internet that you can use to hone your skills.

4. Can I learn data science without experience?

Yes, it is possible to learn data science without any experience and many have done so. The courses listed here will help, as they take you through right from the basics. A lot of hands-on practice also helps.

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