The demand for data science professionals is soaring around the world. Over the past few years, the adoption of data science across the world has grown tremendously. This increasingly positive outlook for data science offers a promising data science career opportunities. This is a golden opportunity for people to learn data science and enter the workforce. However, this is easier said than done. 

 Learning data science 

 Data science is a multi-disciplinary field. To work effectively as a data science professional, you need to know multiple subjects including mathematics, statistics, computer science, software engineering, and much more. The most essential part to learn as a data scientist is to learn to solve problems. Problem-solving is an essential part of nearly all high-stakes roles. The difference is data scientists rely on data to solve problems, while others do so based on previous experience or mere guesswork. Data provides a more accurate picture of a situation than guesswork can ever tell. 

 Statisticians come closest to data scientists. Except much of the work of statisticians have now been automated by programming. Thus, to learn data science people are expected to have a strong understanding of statistics and programming. Statisticians performed statistical techniques on Excel or other standalone tools. With the introduction of Python and its libraries, statistical techniques – finding results, analysis, data visualizations, and predictions – are done using Python. Libraries like NumPy, Pandas, Sci-kit, and SciPy, have made working with large data easier and faster. Techniques that earlier took hours can be performed in a few minutes. All in all, the only difference between earlier and now is the work of statisticians has been sped up.  

 Data scientists require a tremendous amount of practice before they become one. Most data science projects at companies are aimed at solving critical business problems that require out-of-the-box thinking to help companies solve their problems. Before one reaches that level, aspirants should practice on various data science projects. Most data science aspirants practice on platforms like Kaggle, Data Driven, etc. Some even participate in data science research at universities or take extended internships before they can join a full-time data science role. 

 The present times, when most people are at home, is an opportunity for data science aspirants to learn data science online and progress towards a data science career. 

 Learning data science online

 Primarily, there are three ways for aspirants to learn data science online-

1. Online university degrees  
2. Online data science certifications
3. Online community 

 Online university degrees 

 Many universities offer a master’s degree in data science. However, compared to traditional programs, these are online. These programs can be cost-prohibitive, given shorter lengths of programs and the amount of dollars required to be invested. However, the bright side is you will be well-regarded by employers. Several universities offer online data science degrees. You can research and find a program that suits you the best. Many programs even take aspirants with no programming background. So check the program that suits you best. 

 Online data science certifications 

 Some online platforms offer flexible, self-paced, and industry-validating data science certifications. These programs allow you to learn at your own pace, while still maintaining your full-time employment. You can learn, work, and do practical projects as and when you have time. The following are a few popular data science certification programs — 

1. Coursera 

 It offers an online data science certification in collaboration with John Hopkins University. As part of the program, you will learn Python and R programming, data analysis, regression, data cleansing, data manipulation, exploratory data analysis, cluster analysis, and more. The program culminates with a learner submitting a data science project. The program is further expanded to specialization and allows learners the flexibility to choose a specialization from statistic inference, data product development, machine learning, and a few more. 

 This program is free. Learners can view the content of the program without paying. However, to get a certificate, you will need to pay. 

2. Data Science Council of America (DASCA) 

 DASCA is an independent certification body and offers a slew of certifications for all-levels of data science professionals. These are vendor-neutral and globally-recognized certifications that validate the holder’s proficiency in various data science skills. The platform offers ABDA (Associate Big Data Analyst) certification program for beginners who want to break into the data science industry. As part of the certification, you are validated for your proficiency in R and Python, data visualization, machine learning, in-memory analytics, Spark, Flume, Pig, deep learning, mobile and social analytics, and more. 

ABDA is amongst the best data science certifications for aspirants who want to start a career in data science. The platform also offers ABDE, SBDE, and SDS certifications meant for data engineers and experienced data scientists respectively.  

3. Udemy 

 This online learning platform offers several short-duration data science courses. 

You will need to pick several individual courses on statistics, programming, data analysis and manipulation, predictive modeling, and more to complete data science. Courses are comparatively inexpensive on this platform. 

All courses are paid and you need to pay upfront before you can access the content. 

Online community learning 

The Data Science community is constantly growing. Experienced data scientists offer all possible help to aspiring data scientists to learn. Several Facebook groups are dedicated to learning data science, where seasoned data scientists share lessons, tutorials, and other resources to help aspirants and clear confusion. 

 Similarly, YouTube has a large number of channels where professional data scientists share tutorials related to complex topics to help beginners get a better understanding. Interacting with these people helps expand the breadth of knowledge and clear doubts and confusion. 

 All in all, there are several online platforms where you can learn data science. They might not be a fit for everyone, but given sometime one can easily adapt to learning online. If a dedicated effort is put in learning and working on projects, data science can be learned as effectively as in-person training.