Overview
The role of data scientist is rapidly rising in the IT sector. Glassdoor’s job-market trends back up the claim that this is the best job available today. This year, the world will require 5 million data scientists. The need for data analytics is only expected to grow as the volume of data created and stored continues to expand at an exponential rate. Data scientists will continue to be in high demand as businesses seek to use big data to gain competitive advantage.
A data science certification can open many doors in the job market. Data science courses can help anyone, from recent graduates looking to make a splash in the job market to seasoned pros hoping to broaden their horizons, acquire the knowledge and experience sought by today’s top employers.
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We’ve compiled a list of the top 2023 certifications, courses, and programs in data science from recognized universities and other reputable sources. Thousands of students and professionals have benefited from these online, accredited, and widely-recognized free and paid data science resources and certificate programs.
Best data science programs online
IBM Data Science Professional Certificate (Coursera)
To better prepare students and professionals for careers in data science, IBM has created and is offering a certification program through the Coursera platform. Data science and machine learning are disciplines that benefit greatly from hands-on, practical experience.
This is one of the top Data Science Programs, and it consists of 9 courses covering a wide range of data science topics, including the basics of data science, open source tools and libraries, data science methodology, Python programming, a familiarity with databases and SQL, data analysis and visualization with Python, the fundamentals of machine learning, and a culminating applied data science capstone project.
The average time commitment per module in any of the nine courses is between two and four hours. For a total newbie, the program could take up to two or three months to finish. A Certificate and IBM open badge (actually 9 IBM badges for each of the 9 courses included in the program) attesting to your proficiency in data science will be presented to you upon successful completion of this data science training.
Data Science Specialization — JHU @ Coursera
This collection of courses is one of the most popular and highly regarded options available. The curriculum at JHU strikes an excellent balance between breadth and depth. This series includes a comprehensive introduction to statistics, the foundation of data science, which is often left out of traditional data science courses.
The Data Science concentration offers a wonderful equilibrium of theoretical study and practical experience with the R programming language. You should be familiar with Algebra and have prior programming experience (preferably in R, but not required). A familiarity with Linear Algebra and/or Calculus is helpful but not required.
Applied Data Science with Python Specialization — UMich @ Coursera
The University of Michigan, which also offers a Master’s in data science online, is responsible for this outstanding concentration on the practical aspects of the field. This means you will be exposed to and given practice with some of the most popular Python libraries used in the field of data science, including matplotlib, pandas, nltk, scikit-learn, and networkx.
While the statistics necessary for data science and the origins of specific machine learning algorithms are outside the scope of this series, a thorough discussion of how to implement and assess these methods in Python is provided. Given this, I would recommend this book only to someone who is already familiar with R and/or is learning the statistical concepts elsewhere.
The Statistics with Python Specialization is a good place to start if you need a refresher course in statistics. Many of the most crucial statistical abilities for data science will be ingrained in you.
Dataquest
Dataquest is a great tool for learning on its own, but it’s also a great supplement to the other online courses here.
Dataquest dispenses with the use of video lectures in favor of a kind of interactive textbook. Each section of the data science path includes a set of browser-based interactive coding exercises designed to help you put what you’ve learned into practice.
Dataquest stands out among other interactive platforms because of its well-structured curriculum, the opportunity to gain experience with real-world data science projects, and the availability of a friendly and helpful Slack community where questions can be asked and answered.
Python for Data Science and Machine Learning Bootcamp — Udemy
A great value for the cost of the course. The instructor does a great job covering the fundamentals of data science, including Python, visualization, and statistical learning. The assignments are a huge plus compared to similar courses on Udemy. You will be given exercises to complete in your own time using Jupyter notebooks, with the instructor providing a video solution to each problem.
There is no statistical analysis covered in this course because of its emphasis on practical applications. It is recommended that this course be taken in conjunction with another course in statistics and probability.
The Udemy course “Data Science A-Z” also deserves recognition for its usefulness. Although I appreciate the breadth of Data Science A-Z’s coverage, I don’t think it meets the criteria as well as Python for Data Science and Machine Learning Bootcamp because it employs tools from outside the Python/R ecosystem.
Professional Certificate in Data Science from Harvard University (edX)
Harvard University’s Online Data Science Certificate Program is provided by edX, the world’s largest and most established online university. You’ll get a head start on your data science career by learning foundational skills like R programming, machine learning, and more through application to real-world case studies.
This is a highly regarded, intensive, and time-flexible program that can be completed in 2–4 months. This program is very accessible, affordable, and flexible because it consists of 9 graduate-level courses taught by Rafael Irizarry, a professor of biostatistics at Harvard, and is offered entirely online at a fraction of the cost of traditional college. This data science curriculum consists of 9 courses: R Fundamentals, Data Visualization, Probability, Inference, and Modeling; Productivity Tools; Wrangling; Linear Regression; Machine Learning; and a Capstone project. Thus, you’ll start with the fundamentals and end with a Capstone project in which you put everything you’ve learned to use in solving a real-world issue. After completing the course, participants will be able to work on a data analysis project on their own.
Successful graduates can highlight their Professional Certificate in Data Science when applying for jobs.
Applied Data Science with Python Specialization by University of Michigan (Coursera)
Four University of Michigan professors collaborated on this Coursera Data Science program. The course is designed to help students with a fundamental knowledge of programming manipulate and gain insight from data. There are a total of 5 classes here that cover the fundamentals of data science with the Python language. Students should come into this course with some familiarity with programming, preferably in Python. Statistics, machine learning, data visualization, text analysis, and social network analysis are just some of the topics covered in this course. It instructs students in the use of well-known python libraries for data analysis, including pandas, matplotlib, scikit-learn, nltk, and networkx. The five courses are as follows: Intro to Data Science with Python; Applied Plotting, Charting, and Data Representation with Python; Applied Machine Learning with Python; Applied Text Mining with Python; and Applied Social Network Analysis with Python. Students who wish to earn the specialization certificate must first complete all five courses.
Google Data Analytics Professional Certificate
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In March of 2021, Google introduced the Data Analytics Professional Certificate. Since there was a severe shortage of qualified Data Analytics professionals, resulting in financial losses for businesses due to inefficient data utilization, this development could be said to have occurred at the most opportune time. Your job as a Data Analyst (or Data Scientist) is to sift through mountains of information in search of insights that can inform business decisions. In the United States, there are about 337,400 open positions for data analysts and the starting salary is $67,000.
Harvard Edu Data Science and Machine Learning
The most widely used methods in Data Science have their roots in Machine Learning. It’s a set of procedures that lets computers draw conclusions about the future based on past data. Spam filters, speech recognition software, movie recommendation engines, etc. are all examples of useful applications.
Data Science and Machine Learning Program by Scaler
Scaler – InterviewBit’s Data Science and Machine Learning program is one of the most well-liked online courses in the field, and it was developed with input from advisors at the top 50 tech companies. Working on real-world projects and getting immediate feedback from experts in your field is a major benefit of this program. You’ll be ready to take on the most difficult Data Science and Machine Learning problems, as well as real-world business projects, thanks to the course’s well-structured modules and emphasis on hands-on practice. It has a high rating and is a popular option among students.
Advanced Program in Data Science by IIM Calcutta
Students will learn how to collect, organize, analyze, and interpret data in various ways throughout the course of this program. Professionals in the workforce who want to learn by doing will find this course particularly useful. SPSS Modeler, Oracle SQL, Tableau, Python, @Risk, R, Hadoop, Arena, etc. are just some of the data management and analysis programs that you’ll learn the basics of in this course. Students who successfully complete the program will be equipped with the knowledge and skills necessary to apply sophisticated quantitative techniques and methods.
Data Science Specialization from Johns Hopkins University
This course will provide you with an overview of the fundamental concepts and tools required for a career in data science. In the culminating capstone project, you’ll apply what you’ve learned by developing a data product using real-world information. You should have prior programming experience (not necessarily in R) and a solid grasp of algebra. Knowledge of linear algebra and calculus would be useful but is not required. Successful course graduates will be able to showcase their expertise with a polished portfolio.
FAQs
What is Big Data?
Big data is defined as data sets so large that they defy traditional methods of data management and analysis. This can be an issue for businesses that routinely process petabytes of data.
Big data may be covered in the general data science curriculum, or you may choose to focus your studies and earn credentials in this area.
Schools don’t grant degrees in the field, but students majoring in computer science or technology frequently take courses in it.
Are certificates worth it?
In contrast to Udemy, platforms like edX, Coursera, and Metis typically feature courses taught by university faculty and offer certificates to successful students.
It’s worth noting that edX and Metis certificates are among those that qualify for CEUs. However, if you want access to features like graded assignments and exams, you’ll need to pay for an upgrade. Committing to a certificate also puts money on the line, so you’ll be less likely to quit if you need extra motivation to finish the course. Certificates have merit in the eyes of the individual, but they carry little weight with most employers.
What Can I Do with a Master’s in Data Science?
A master’s in data science could open doors to a wide variety of careers. A career in analysis, programming, computer science, or database administration is available to those who prefer to work from a desk.
If you’re looking for a job where you can put your imagination to use, consider becoming a web developer, software engineer, or applications architect. You could also go in an untraditional direction and specialize in data science as a statistician or economist.
Conclusion
Studying and working in the field of data science opens up a world of opportunity. To become the kind of data scientist that companies are eager to hire, you’ll need to put in more time and effort than the hyped-up YouTube videos would have you believe.
Have fun with your studies, and thanks for reading!
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