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Introduction To Data Science

Instructor Led Training Program (Online)

  • Duration 45 day
  • 90 Hour(s)
  • Level: Beginners
  • Assignments and Exams
  • 7 Course(s)
  • Live Industry Project

Fee : Rs 10
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Overview

Data Science is the process of extraction of Actionable Insights from vast volumes of Raw Data i.e. both structured and unstructured.
It is a concept to unify statistics, data analysis, informatics, and their related methods in order to understand and analyze actual phenomena" with data. It uses techniques, methods, processes, algorithms,systems and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. It is related to data mining, machine learning and big data.
About the Program : The online course on data science is a one-stop solution for all your data science learning needs. It offers you complete guidance and tutorial with experience teachers, downloadable resources, hands-on learning experience and job/ internship consultancy.  



Fee : Rs 10
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Course Contents

Python is the most popular language used in Data Science. In this section, our instructors will take you through the basics of Python and areas where it can be used. You will learn how to use some of the popular tools for Data Analysis such as Numpy, Pandas, and Matplotlib. So Module 1 includes the following :

01.Environment set-up
02.Basic Python Coding
03.Array, Functions, File Input
04.Jupyter overview
05.Python Numpy
06.Python Pandas
07.Python Matplotlib

Inferential statistics allows you to make predictions ("inferences") from that data. With inferential statistics, you take data from samples and make generalizations about a population :

01.Normal distribution
02.Test hypotheses
03.Central limit theorem
04.Confidence interval
05.T-test
06.Type I and II errors
07.Student's T distribution

Machine learning is a key component of any Data Science syllabus. It involves mathematics and algorithm models to help students understand how a machine learns and adapts to everyday changes :

01.Fundamental statistical concepts
02.Statistical analysis
03.Modeling methods
04.Logistic Regression
05.Supervised machine learning
06.Unsupervised machine learning
07.Clustering Assignment (Optional)

Text Mining or Text Analytics uses Natural Language Processing (NLP) to convert unstructured texts in the database and documents into normal and structured data that can be analyzed or used to drive machine learning algorithms. Concepts covered in this subject area:

01.Handling unstructured text data
02.Tokenization and vectorization of text data
03.Natural Language Processing
04.Supervised & unsupervised text classification
05.Supervised machine learning
06.Unsupervised machine learning
07.Sentiment analysis of social media data

project related practical..

Project related test ...

When working with data, the knowledge of statistics is necessary and an important skill set that you must have. In this module, you will learn :

01.Basic About Statitics
02.statistical concepts used in data science
03.Difference between population and sample
04.Types of variables
05.Measures of central tendency
06.Measures of variability
07.Coefficient of variance
08.kewness and Kurtosis

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    Application Process

    Candidates can apply to this Introduction To Data Science in 3 steps.

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    Admission

    After the payment is completed, the application will be finally approved and you can start learning.

    Live Industry Projects View All Projects

    Library Management System

    Library management system project website used to maintain all activities of library system such as maintain books stock, issue book records, return book records, student detail and also keep data of penalty for late return books. The project covered all activities which have done to run the library system. 

    E-Governance Project

    e-Governance refers to the use of Information and Communication
    Technologies to improve the Transparency, Accountability, Efficiency & Effectiveness of Government.

    • Doing things differently, and not doing different things…
    • Re-engineered process perspective
    • Citizen and service-centric approach, and not a department centric
    • ICT Enablement
    • The back-ends and in parallel creating suitable middleware
    • community access points.

    Virtual Laboratory

    Virtual Laboratory is a computer-based activity where students interact with an experimental apparatus, hands-on or other activity via a computer interface.
    IT is also can be referred as an on-screen simulator or calculator that helps test ideas and observe results.  Virtual Labs enable the students to learn at
    their own pace and enthuse them to conduct experiments.
    Virtual Labs also provide a complete learning management system where
    the students can avail various tools for learning, including additional
    web resources, video lectures, animated demonstration, and
    self-evaluation.

    Our future plan is to use technologies like VR, AR, Meta Phase like technologies to make the feel of the experiments much more better.

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