The emergence of data science as a multi-faceted discipline has brought about a complete transformation in the modern IT landscape. With its ability to mine structured/unstructured information, extract actionable knowledge, and provide deep insights, data science has rendered itself valuable to both, individuals and businesses.
This is why it comes as no surprise that the revenue generated worldwide from data science and big data analytics has increased from $122 billion in 2015 to $189 billion in 2019. It is further likely to reach a magnificent high of $274 billion by 2022.
With the rise of data science as a distinctive field of study, the need for well-trained data science professionals has also begun to witness a massive upsurge. Numerous educational institutions, offering courses as varied as master’s degrees, post-graduate diplomas, multi-day workshops, certificate programs or online tutorials have started dotting the horizon.
In such a situation, choosing a comprehensive data science course that harbours the potential of leveraging your career can often turn out to be a highly challenging task.
If you too are wondering which data science course in India can effectively equip you to meet your professional needs, here are 3 credible steps to help you identify the specific data science training that you need.
To begin with, figure out the precise aim that you intend to fulfil by getting a data science certification. What specific role are you opting for? Are you an individual who is looking for a career in data science, machine learning, and analytics, or are you a business that is hoping to employ data science for better decision making? You might also be a working professional who is seeking a long-term career transition. Based on your requirements, determine which data science jobs would boost your prospects the most, and outline a road-map that would help you streamline your targets.
Whether as an individual or as a business, you need to possess certain skills that determine your aptitude to learn data science from scratch. In case you don’t have them, identifying your skills gap and choosing a data science degree that helps you bridge it, becomes extremely necessary.
The skills you require largely include:
•Analytical skills – to interpret data, trace trends and develop patterns by constructing predictive models, conducting data analysis, devising evaluation metrics, and producing data visualisations.
•Communication skills – to understand ‘data to decisions’ framework and implement it via initiating collaboration, developing consensus, providing guidelines, and offering thought leadership.
•Mathematical skills – to ensure that the factual objectivity of data remains intact, you need to be proficient in algorithms, information retrieval, linear algebra, statistics, multivariate calculus, and machine learning techniques.
•Technical skills – to pull and collate data, you should have adequate knowledge about the SQL framework, Python, Java, Microsoft Excel, C++, Tableau, and other similar coding and programming skills.
Apart from the aforementioned, you should also be well-versed in advanced data science techniques like profiling, segmentation, trend analysis, A/B testing, neural networks, decision trees, etc. These skills would prepare you to seamlessly integrate different business verticals under the shadow of a competent, measurable, and empirical umbrella.
Based on your intended objective and the gap you want to fill, choose a data science program that meets your requirements in the best possible way. For instance, if you have no prior experience but are looking at a future as a data scientist, you need to enrol for a master’s degree. It is the best course of action for individuals who want to learn data science basics. On the other hand, certificate programs, professional workshops, and online tutorials are most suitable for businesses that plan on enhancing the efficacy of their workflows. However, make sure that the program you finally select includes a specialisation in applied knowledge and real-time project handling.
Considering that 80% of data would be unstructured in the next 5 years, finding appropriate ways to derive inferences from it has become a global priority. The only way to qualify for a chunk of this ever-growing industry is to attune yourself to the demands arising out of evolving technology.
After all, data science is a discipline of the future and gaining competence in it equips you to immediately increase the productivity of all your operations and processes!