Today Lets see the skills necessary for starting or continuing your carrier in the domain of Data Science.
Road Map:

1. Determine what you want to learn — Because there are many roles in Data science.
we’ll take a look at some of the more popular data science jobs, what they do and the skills they require to be successful — so you can determine which one is right for you.
• Data Analyst
• Data Scientist
• Business Analyst
• Software engineer
• Marketing Data Scientist
• Machine Learning Engineer
Each of these roles includes some common and different Responsibilities, programming Languages, Tools and skills.
Each industries uses different combination of Data scientist.
2. Enroll in a data science program — organized data or syllabus (Plan).

Select a data science course which is or who are very caring and provides good feedback or respond immediately because most of them promise to provide you guide and placement, but most of them don’t keep up to their word though your performance and learning is really good.
Just find out the course or program which is having good reviews from more number of Students/Paced Student.
3. Polish Math Skills (Revision) — Revise your math's basic and Athematic Aptitude

Basic Math Skills
Revision of math skills, because math is one of the basic and most important part of data science which you should and must have through you're carrier
4. Learn Statistic and Probability —math that focuses one stats and probability.

This is going to be the major part of your studies in Data Science, so start revising all the concepts and learn the formulas.
5. Get in to Programming — Python, R, Java and etc.

If you are new to the programming domain, It is time to get your hands and Brain working and programming is not that tough as you think, it is just as easy if you start practicing it again and again.

6. Tools — Get to know different Data Science Tools because these are the most powerful tools you can use to play with the data and research, some of the are Excel, Tableau, SAS, Power BI, MATLAB, Jupyter, Scikit-learn, TensorFlow and etc.

7. Work on Projects and Keep Practicing — Projects are the most important part in your data science course or program because companies that hire you look for projects you have done and also they might judge you based on your project, I would personally suggest you to work on many projects and mainly projects with live or Real world data something that impresses other data scientists which makes them connect with you (Kaggle is one of the best place to start).

8. Internship — Most important part of the course is Internship, Look for internship which provides you good mentor and study material to start your project and also very importantly look for top Company Internship with the most reputed status in Data Science.
So here the 9th, 10th and 11th points are all similar or one process which is Make a good network with Internship mentors and students and be in touch with them more than your other friends, because all of you are traveling in the same ship, So make good Network and create your self a market ready or Job ready portfolio with all your experience or works you have done to find a job, Data Science Jobs are mostly looking for experienced candidate, but with a good Portfolio you can get into it.

By Asad Ullah Masood

Thank you!

Author Of article : Asad Ullah Masood Read full article