Skills and online courses to become Data Scientist, the most important position in the world by 2025

Data analyst and data scientist positions are expected to be the best in the world by 2025. Here is a list of the skills you need and the online courses you can try to break into this industry.

Data analyst and data scientist positions are expected to be the best in the world by 2025. Here is a list of the skills you need and the online courses you can try to break into this industry.

According to the World Economic Forum’s Future of Jobs report published in 2020, the highest position in the world – with the highest demand – will be that of a Data Analyst and Scientist by 2025. The pandemic-induced digital transformation has led to an increased demand for data science skills, where employers are willing to pay a premium, along with other long-term benefits and incentives, in order to attract and retain scientists. and data engineers.

The demand for data scientists exceeds the global supply, and India is no exception. The field offers enormous opportunities to take one’s career to the next level, opening access to various positions such as – Data Scientist, Data Architect, Data Engineer, Data Analyst, Business Analyst, Analytics Manager and Business Analytics Specialist.

Data science competence is not limited to learners and professionals in STEM fields. It’s not uncommon for companies around the world to create data science teams with talent drawn from a wider range of fields – including social sciences – alongside traditional hires like IT people, thus creating opportunities for a diverse set of professionals to secure data science jobs.

According to Coursera’s Global Skills Report 2021, learners can prepare for an entry-level data analyst position with just around 64 hours of e-learning sessions.

Here is a list of essential skills and online courses in data science that learners can choose from:

1. Python programming

  • Programming for all (Introduction to Python) by the University of Michigan
  • Python for Data Science, AI and Development by IBM

2. Statistics

  • Statistical inference by Johns Hopkins University

3. Machine learning

  • Machine Learning by Stanford University

4. Probability and statistics

  • Probabilities and statistics: at p or not at p? by the University of London
  • Introduction to Probability and Data with R by Duke University

5. Machine learning algorithms

  • Machine Learning Algorithms: End-to-End Supervised Learning by the Alberta Machine Intelligence Institute, University of Alberta
  • Artificial Intelligence Algorithm Models and Limits by LearnQuest

6. Applied machine learning

  • Introduction to Applied Machine Learning by the Alberta Machine Intelligence Institute, University of Alberta
  • Applied AI with DeepLearning by IBM
  • Applied Machine Learning in Python by the University of Michigan

7. Data management

  • Data Management and Visualization by Wesleyan University
  • Prepare the data for exploration by Google

8. Econometrics

  • Econometrics by HSE University
  • Econometrics: methods and applications by Erasmus University Rotterdam

9. Deep learning

  • Neural Networks and Deep Learning by DeepLearning.AI
  • Introduction to Deep Learning and Neural Networks with Keras by IBM

10. SQL

  • SQL for Data Science by University of California, Davis
  • Databases and SQL for Data Science with Python by IBM
  • Introduction to Structured Query Language (SQL) by the University of Michigan

Read: 5 Tips to Start Your Data Science Career

Read: Over 93,500 data science jobs vacant in India: study

Read: Career as a Data Scientist: Scope, skills required, job profiles and other details

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