By Mukund, Akilesh | 25th December, 2020 | 5 min Read
Since you are here chances are that you are at least interested in learning Data Science and that is a great thing. The word Data Science itself is a buzz these days and the number of people aiming to become a data scientist is more than ever. But the path for this is much simpler than before. Although a formal degree has a different impact, it is not a mandatory thing. Anyone can start learning through data science online courses and become an expert in the field.
"Data Scientist is the Sexiest Job of the 21st Century."
says Harvard Business Review. And looking at the current scenario, this is the best time to learn data science online courses, and if you are wondering or stuck at the question - where to start from or what to learn, don't worry, you are at the right place. We got you covered.
Online courses can be the best resource to learn good stuff, right from basic technologies like C and Python to complicated courses like Machine Learning and Data Science. Keep reading this article to know about the best data science online courses.
If you are looking to pursue a career in data science, then probability and statistics is one thing you should be aware of. Probability and Statistics are essential to get into data science. Making predictions and finding the structures in data and are important parts of data science.
In addition to the data science online courses listed below, I would suggest you read these books to learn statistics for data science. You can access a few free statistics books for Data Science here.
This is one of the best data science specializations out there. The courses are taught in R by Professor Rafael Irizarry (Professor of Biostatistics at Harvard). Because the instructor is a statistician, he delves into lots of statistics which really provides a solid foundation. The lectures are to the point and are as short as they can and still give you the needed information. The course covers the fundamentals of Rand and data visualization techniques which includes data visualization with ggplot2 and data wrangling with dplyr. With the ML course, you learn some of the standard classification and regression techniques, cross-validation and model tuning with caret, regularization, and applications on the MovieLens dataset. And finally, you get to do a capstone project. Overall this is an excellent course and covers all the essential things you need to know.
This is an ideal course for beginners who are looking to learn data science. It has 9 courses which will expose you to the latest tools and skills used in the industry. You will learn various techniques including data visualization, data analysis, statistical analysis, predictive modelling, and machine learning algorithms. And more than all this, you'll get to work on real-world projects using real data science tools and real-world datasets. Except for the first course, all other courses have a good number of hands-on-lab sessions using IBM Cloud. And on completion, apart from the professional certificate you get from Coursera, you'll also receive a digital Badge from IBM recognizing your proficiency in Data Science
While the above courses are more academic-oriented, this is more of a practical oriented course. You start with the basics of python and get to learn various data manipulation and visualization skills as you go along. The course has a lot of small assignments which are really fun to do. Although the program says it has 23 courses, don't be scared. They are very short and can be completed very quickly. If you are looking to get your hands dirty then this is the right course for you.
This is a fantastic course focused on the application side of Data Science, meaning you can expect a good introduction to python libraries like matplotlib, pandas, nltk, scikit-learn, and networkx. You will also get hands-on experience on how to implement these libraries on real-world data sets. The exercises are pretty good and make you proficient in the above libraries. The program requires elementary knowledge in statistics and math, but nothing too advanced. As hinted by the word "Applied" in the title, the course doesn't provide you with a deep level of theoretical concepts. But it gives you just enough theory to understand the exercises. Overall this course makes you enough ready to go out and apply data science concepts in the real world.
This is one of the most immersive courses you can find on udemy. The course starts with a python crash course which is more like an introductory course to aid the understanding of other lectures in the course. Going forward you'll get to learn data analysis and data visualization libraries and machine learning algorithms. While the data analysis and visualization sections cover libraries like Numpy, Pandas, matplotlib, Seaborn, Cufflinks, Machine Learning section covers various algorithms like Linear Regression, Logistic Regression, K Nearest Neighbors, Support Vector Machines. The Machine Learning section also covers some advanced concepts like Natural Language Processing and Neural Networks. The best part of this course is that the structure is quite easy to follow. It moves from theory to hands-on practice. The instructor doesn't simply ignore difficult concepts. He breaks down difficult concepts into smaller, more digestible concepts and goes deeper into these concepts. This helps in fully understanding the concepts. The extra reading material is also pretty good to explore.
Before you choose the best data science online course, it is important to know about the various job roles in data science. Data Science does not end with being a data scientist, there are many other data science roles that are important for an organization such as data analyst, data engineer, statistician, machine learning engineer and so on. I have made a consolidated list of various job roles in data science. You can read the full article at https://www.qwakho.com/data-science-as-a-career-start-a-career-in-data-science
The next step before you choose a data science online course, it is important to assess your current skill level, The first step to learning is to know what you are aware of and what you are not and being determined to take up a prerequisite course and learn the basic concepts before you take up the actual course.
Read the course description and make sure the content of the course satisfies your requirements. Take up the course seriously and think about the time and effort that you're willing to put into upskilling yourself in data science and analytics.
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