How do non-tech professionals acquire the necessary technical and analytical skills required to thrive in data science field?

Question

How can non-tech professionals develop the technical and analytical skills required to succeed in the field of data science?

Answer 1

Non-tech professionals acquire essential technical and analytical skills for success in the data science field through a combination of formal education, online courses, certifications, practical projects, networking with industry experts, participation in internships, continuous practice, and seeking mentorship. These pathways enable them to develop the expertise needed to excel in data analysis, machine learning, and data-driven decision-making.

If you are interested in getting into this field, check out this video about Sami Khan and how he achieved a career transition from an HR Recruiter to a Data Science Expert with the help of Intellipaat’s Data Science Course.

Answer 2

Complete guide for non-technical professionals: 

Step 1: Develop Good Basics: Mathematics, Probability, Statistics, and Linear Algebra are important tools for data analysis and there are some free resources like Intellipaat blogs and StatQuest that can help. Basics of Data Science: These include the very elementary knowledge of data wrangling, EDA and visualization. Courses available on Intellipaat are sufficient for this. 

Step 2: Start With Python: If you look around, Python is the one language that you see everywhere in data science. You can find many tutorials of python on youtube available for free.

 Step 3: Learn how to use Pandas and NumPy for data manipulation and analysis. Get used to using Matplotlib or Seaborn for data visualisation. 

Step 4: Understand how linear regression, decision trees, clustering, and any other key machine learning algorithms work. Kaggle has such problems that one can sense the need to solve. 

Step 5: Engage in some real world projects and host them on GitHub. This is important in order to be able to build a portfolio that you can present during a job interview.