• Data Scientist
  • Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data.A data scientist is an analytics professional who is responsible for collecting, analyzing and interpreting data to help drive decision-making in an organization.

    Various skills required for becoming a succesful Data Scientist are as follows:

    i. Python,C++,C

    Programming languages, such as Python or R, are necessary for data scientists to sort, analyze, and manage large amounts of data (commonly referred to as “big data”). As a data scientist just starting out, you should know the basic concepts of data science and begin familiarizing yourself with how to use Python,C++,C,etc.


  • Java Course(with DSA) : https://bit.ly/
  • Complete C Course : https://bit.ly/FullTutorialC
  • C++ Course (DSA) : https://bit.ly/
  • ii. R

    R is one of the most pervasive and well-used languages in data analytics. One poll conducted by the Institute of Electrical and Electronics Engineers’s (IEEE) professional journal, Spectrum, found that R ranked fifth in a list of the top ten programming languages used in 2019.R’s syntax and structure were created to support analytical work; it encompasses several built-in, easy-to-use data organization commands by default. The programming language also appeals to businesses because it can handle complex or large quantities of data.


  • Data camp - https://www.datacamp.com/courses/free-introduction-to-r(paid)
  • Great learning - https://www.mygreatlearning.com/academy/learn-for-free/courses/introduction-to-r (paid)
  • iii. SQL and NoSQL

    there are several database languages that you will need to be familiar with Structured Query Language, better known by its acronym, SQL.SQL persists as the standard means for querying and handling data in relational databases.


  • Coursera :Beginner : https://www.coursera.org/learn/introduction-to-nosql-databases , Advanced : https://www.coursera.org/specializations/nosql-big-data-and-spark-foundations
  • Great learning - https://www.mygreatlearning.com/academy/learn-for-free/courses/introduction-to-r (paid)
  • 2.Statistics and probability :

    In order to write high-quality machine learning models and algorithms, data scientists need to learn statistics and probability. For machine learning, it is essential to use statistical analysis concepts like linear regression. Data scientists need to be able to collect, interpret, organize, and present data, and to fully comprehend concepts like mean, median, mode, variance, and standard deviation. Here are different types of statistical techniques you should know: Probability distributions, Over and under sampling , Bayesian (or frequency) statistics.


  • Udemy : https://www.udemy.com/course/statistics-probability-for-data-science/
  • 3.Machine Learning

    You can forecast how many clients your company will have based on the previous month’s data using linear regression. Later on, you can boost your knowledge to include more sophisticated models like Random Forest. Some machine learning algorithms to know include: Linear regression,Logistic regression,Naive Bayes,Decision tree,Random forest algorithm,K-nearest neighbor(KNN)- K means algorithm.


  • Google (FREE) : https://developers.google.com/machine-learning/crash-course
  • Top Universities: https://www.freecodecamp.org/news/best-machine-learning-courses/
  • 4.Data visualization

    With strong visualization skills, you can present your work to stakeholders so that the data tells a compelling story of the business insights. Familiarity with the following tools should prepare you well:Tableau, Microsoft Excel, PowerBI


  • Internshala : https://trainings.internshala.com/excel-course/?utm_source=Google-Search&utm_campaign=CT-Search
  • 5.Cloud computing

    cloud computing tools that help you analyze and visualize data that are stored in cloud platforms. Some certifications will specifically focus on cloud services such as: Amazon Web Service (AWS), Microsoft Azure , Google Cloud


  • Udemy : https://www.udemy.com/topic/cloud-computing/
  • Intellipaat : https://intellipaat.com/course-cat/cloud-computing-courses/
  • 6.Interpersonal skills

    interpersonal skills you can build upon:Active listening, Effective communication skills, Sharing feedback, Attention to detail, Leadership, Empathy, Public speaking.