Data scientist is one of the highly trending designations, IT professionals aspire to transit towards. Not to mention the hefty salary package it comes with, aside from that there’s a certain roadmap one needs to follow to strengthen their chances at being selected. To become a competent data scientist in 2021, these skills are prerequisites or data scientist qualifications that need to be honed beforehand.

1. Statistics

2. Python/R (Programming language for coding, and analysis)

3. SQL (Structured Query Language for transforming databases and saving programming time with the use of concise commands)

4. Machine learning and Artificial Intelligence (Algorithms and data usage to mimic how humans learn. Concepts include time series, reinforcement learning, outlier detection, supervised and adversarial learning, computer vision)

Enrolling in a data scientist course would assist the aspirants to not only gain technical knowledge but also get certificates upon completion of their syllabus.

Technical knowledge for becoming a Data scientist
1. Calculus & Linear algebra (for building machine learning models, plotting and finding function values)

2. Statistics (for insights related to actionable data, plus exploring and understanding data precisely. Checking data anomalies)

3. Probability (for doing further analysis and estimation, example: identifying variable relationships and dependencies, future trends prediction)

4. Data wrangling (presenting data to businesses for taking action on)

5. Programming language (Julia, Python, R, TensorFlow, Scala, SQL)

6. Data visualization (via pie charts, bar charts, scatter plots)

7. Data management (via Oracle, MySQL)

8. Soft skills (improving interpersonal and communication skills for taking project responsibilities)

9. Business acumen (gaining proper knowledge about the concerned sector, understanding business issues to be resolved)

The right kind of intuition to understand the problem and building solutions creatively is a must.

Some more Data Science skills to master
1. Data cleaning

2. Data ingestion

3. Data analysis (Exploratory)

4. Data pre-processing

5. Decision making

6. Identifying data patterns

Common Data Science Interview Questions you must have answers to
While cracking the interview stage shouldn’t scare you, nonetheless, you should brush up on the basics, as in with data scientist interview questions, you could be asked to explain these concepts or interrogated about some of them.