Data Science using Python

10000 Learners

Course Objective:

Python: On completion of the training, participants will be able to successfully program in python programming language. They Will be able to work on Data Science Algos and will learn Machine Learning .

Course Content:


Introduction to Python
  • Introduction to basic programming language.
  • Concept about Python features.
  • Why Python is considered as Demanding Language in Market
List,tuples,sets,dictionaries in Python
  • Introduction to list, sets, tuples, dictionary
  • Indexing of list and other containers
  • Slicing of list and other containers
  • Operations on List, Tuples, Sets, Dictionary
Introduction to Data Science

Big data, business intelligence, business analytics, machine learning and artificial intelligence. We know these buzzwords belong to the field of data science but what do they all mean?


Learning the tools is the first step to doing data science. You must first see the big picture to then examine the parts in detail.  


You need to think like a scientist before you can become a scientist. Statistics trains your mind to frame problems as hypotheses and gives you techniques to test these hypotheses, just like a scientist. 


Data scientists don’t just need to deal with data and solve data driven problems. They also need to convince company executives of the right decisions to make. These executives may not be well versed in data science, so the data scientist must but be able to present and visualise the data’s story in a way they will understand. That’s where Tableau comes in – and we will help you become an expert storyteller using the leading visualization software in business intelligence and data science.

Advanced Statistics

Regressions, clustering, and factor analysis are all disciplines that were invented before machine learning. However, now these statistical methods are all performed through machine learning to provide predictions with unparalleled accuracy. This section will look at these techniques in detail.  

Machine Learning

The final part of the program and what every section has been leading up to is deep learning. Being able to employ machine and deep learning in their work is what often separates a data scientist from a data analyst. This section covers all common machine learning techniques and deep learning methods with TensorFlow.  

Business Intelligence Tools
  • Intro to BI.
  • Data Science for BI.
  • Project on Real Business Intelligence Scenario.

Key Features

  • Gain skills and competencies required in Industry by Experts.
  • Work on Real-time Projects depending upon the course you select.
  • Students work in a professional corporate environment.
  • Get a globally recognized Certificate form WebTek with our partner logos.
  • Global Brand recognition for Placements.


  • 35- 40 hrs
  • Regular Batches: 1st Yr / 2nd Yr / 3rd Yr / 4th Yr B.Tech. / Diploma students
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