As the plethora of connected devices continues to rise and the Internet of Things (IoT) no longer remains a novelty, the amount of data we generate continues to rise exponentially as well. In fact , data will nearly double in size every two years if current trends continue. It’s no secret that there is an exponential demand for skills in big data and advanced analytics. At NIIT Digit, our Data Science programs are carefully designed to meet the demands for this in-demand skillset.


Statistics for Data Science

  • Descriptive Statistics
  • Statistical techniques for forecasting and variance analysis

Data Engineering

  • Source, Collect, Clean, prepare and store data in a query friendly form
  • Work with different types of database (NoSQL, Graph, Columnar, time series data)
  • Select, query and aggregate data

Data Analysis, Visualization and Business Intelligence

  • Create data visualization using Python and Tableau
  • Build dash boards & Publish

Software Engineering

  • Use Git to manage code repository, code versioning and configuration management
  • Work in an Agile team environment
  • Apply software engineering and clean coding practices

Professional Skills

  • Develop a strong sense of self-efficacy that enables the learner to confidently manage challenges
  • Sharpen communication and articulation skills
  • Collaborate with others for Data Analytics
  • Use effective story telling techniques using data

ML in Data Science

  • Apply appropriate modelling techniques - classification, regression and clustering
  • Use supervised and unsupervised learning
  • Fundamentals of Deep Learning
  • Use tools such as Prometheus & Graffana to monitor ML models
  • Use NLTK for text analytics
  • Understand ML Ops for deploying ML models on the Cloud

Programming in Python

  • Learn and apply structured programming techniques
  • Understand and implement object-oriented concepts using Python
  • Write SQL queries to retrieve, manage, and manipulate data from RDBMSs (MySQL)
  • Utilize appropriate data structures and algorithms to solve problems
  • Working with Numpy & Pandas libraries
  • Complete a non-trivial Python project on statistical analysis of data sets to demonstrate all the skills acquired