Data Scientist

Hi, Data scientists are in demand, and candidates with the right mix of skills will be rewarded with a future-proofed and lucrative career. Here are some things to keep in mind when pursuing a career in data Science. Data is the new corporate currency, as advancing digitisation sweeps every horizontal and vertical market the world over. The impact on the data Science sector is far-reaching and, as a result, a range of new roles and skillsets are in demand. Here are six global trends you need to be aware of. All industries are open, but you should try to specialize:
*Balance robust academic achievements with on-the-job learning
*Data analytics experience is essential, machine learning helps
*The GDPR is increasing data governance demand
*Make sure you have a solid business intelligence foundation
*Keep your technical skills up to date.

Dear Manish,
Well, you can learn in multiple ways, some people learn everything online while some join programs and courses to become a data scientist. I think one needs to cover a certain topics online while certain topics can only be learnt in classroom training module.
Python Basics, Intermediate and Advanced statistics, Probability and Linear Algebra, Linear Regression, Time Series and Cost Function, Types of Data & Exploratory Data Analysis, Collecting, extracting, querying, cleaning, and aggregating data for analysis, Data Sources, Cleaning and Wrangling, Working with APIs and Web Scraping.
These will help you learn the advanced topics of data Science faster and in depth. I would always recommend data Science aspirants to go for a programme which is classroom-based, instructor-led and heavily practice driven. You will come across a lot of institutions, courses, programs that will help you learn data Science. Some are way expensive while some are reasonable. But, one very important thing to keep in mind while you are enrolling for such courses is to know the worth of it in terms of knowledge and what at the end of the course you are developing within yourself. Remember: "80% practical & 20% theory".
Hope this helps.

Programming:
You need to have the knowledge of programming languages like Python, Perl, C/C+, SQL and Java with Python being the most common coding language required in data Science roles. Programming languages help you clean, massage and organize an unstructured set of data. Knowledge of SAS and other analytical tools. The knowledge of analytical tools is what will help you extract the valuable insights out of the cleaned, massaged, and organized data set. SAS, Hadoop, Spark, Hive, Pig, and R are the most popular data analytical tools that data scientists use. Certifications can further help you to establish your expertise in the use of these analytical tools.