It’s always a great idea to enrich your knowledge base about your favourite field of study. Knowledge is not only cumulative, it grows exponentially. Those with a rich base of factual knowledge find it easier to learn more. It also enhances cognitive processes like problem solving and reasoning to a great extent. In today’s times, it is very convenient to gather information about any topic of your interest on the internet. Talking about data sciences, the hottest job role doing the rounds today, there’s a sea of data science courses that are available online that can satiate your desire of earning that most-sought-after certification in data science now-a-days. As most of the data science or any other courseware for that matter, provides you with the peripheral knowledge about the field. Data science being a vast field of applied knowledge, it is best to learn and polish the skills and start applying the learned knowledge into projects and cases of your future professional use. Practical knowledge of data science principles and models is of utmost importance to land a great role in this field. Listed below are some of the popular online data science courses available that one can gain learning from:

• Massachusetts Institute of Technology
• United States Data Science Institute – USDSI
• Stanford University
• University of North Carolina
• Georgia Institute of Technology
• Harvard University

Agreed that the above are few of the many online options available to expand your knowledge about data science and its fundamentals, it is always beneficial to arm yourself with credible practical knowledge about the domain as well.

Interesting ways to boost your Data Science knowledge are listed below:

1. Read academic papers and data science textbooks

Reading academic papers that introduce, compare and contrast algorithms and machine learning approaches will provide you with profound knowledge than any other blog content. It helps to stay on top of new developments within your field and equip you to elaborate on workings of varied algorithms, choose the suitable models for use cases and justify the decision. As textbooks are rightly quoted as one’s best friends, so why not dig into the one that provides a great introduction to data science, machine learning with code included. Even the certified data science professionals invest their time in the textbooks that prepare them for the timely upgrade in the industry. The famous resource from the GitHub repository can be accessed on: https://github.com/rasbt/machine-learning-book . Among other excellent textbooks, you can get your hands-on to “Python for Data Analysis” by Wes McKinney; “Data mining: Practical Machine learning tools and techniques” by Witten, Frank and Hall; “Applied Predictive Modelling” by Kuhn and Johnson.

2. Implement large projects and real-world data science problems

Engaging yourself to applying your knowledge to real-world data science projects, it will hep you develop in-depth understanding in core data science concepts. Kaggle competitions are a great way to put your knowledge to test via challenging projects. Implementation alone does not fully equip you for a data science role. Developing your own project from scratch gives you the liberty to experiment and implement while you learn to swim in foreign waters.

3. Write technical blogposts and share your data science knowledge

Earning the best data science certification is just the beginning of the learning graph in this industry. Sharing your knowledge while writing useful blogposts can help propagate the knowledge and in turn advance your knowledge base manifold. According to the famed Feynman technique, ‘Explaining a topic to someone else is a great way to learn it yourself and strengthen communication skill’. These can also serve as a demonstration to employers that you understand the topic and are knowledgeable in data science.

4. Assist the Industry-experts and take up an internship or part-time job

Never miss on any opportunity of working with a domain specialist when it comes to data science industry as this would provide you with key industry insights and essential knowledge and soft skills to rank higher.

5. Network expansion is the key to a great Data Science role

Underestimating the power of working and collaborating with others can cost you dearly as these collaborations with a fellow data scientist or programmer can teach you skills that online courses might fall short of. Networking exposes you to learning cutting-edge algorithms and technologies and ever new ways of doing things.

No doubt, investing your time, resources and skills into this revolutionary technology domain called Data Science is worth all the effort. From daily routine to pharmaceuticals, Data science has proved to leverage maximum impact on every industry it touches. As the industry experts say that learning data science is hard and perfecting the art of data science skills takes years to gain proficiency. Nevertheless, it’s worth it all!