Data Science Methodology (DS0103EN) Data Science Methodology (DS0103EN)

Data Science Methodology (DS0103EN)

Data Science Methodology (DS0103EN)

Course Provider

Data Science Methodology (DS0103EN)

Course Highlights:

  • Grab your lab coat, beakers, and pocket calculator ... wait what? Wrong path! Fast forward and get in line with emerging data science methodologies that are in use and are making waves or rather predicting and determining which wave is coming and which one has just passed.
  • Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision- making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn:
    • The major steps involved in tackling a data science problem.
    • The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
    • How data scientists think!
  • Co-branded certificate by FutureSkills Prime & SkillUp
  • Eligible for GOVT. OF INDIA Incentives
  • Job Roles:
    • Data Scientist

What will you learn in Data Science Methodology (DS0103EN) course?

In this course you will learn about:

  • The major steps involved in tackling a data science problem.
  • The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
  • How data scientists think through tackling interesting real-world examples.

Data Science Methodology (DS0103EN)

  • skill-type-icon Skill Type
    Emerging Tech
  • domain-icon Domain
    Artificial Intelligence/ Big Data Analytics
  • course-category-icon Course Category
    Deepskilling Course
  • certified-earned-icon Certificate Earned Joint Co-Branded Participation Certificate
  • ssc-assesment-icon Nasscom assessment Available
  • course-covered-icon Course Covered under GoI Incentive
    Yes
    • cost-white-icon Course Price
      INR 2,999
      + 18% GST
    • duration-white-icon Course Duration
      10 Hours
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Why you should take Data Science Methodology (DS0103EN) course?

Fast forward yourself and get in line with emerging data science methodologies that are in use and are making waves or rather predicting and determining which wave is coming and which one has just passed

Who should take Data Science Methodology (DS0103EN) course?

This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address the question at hand. So this course is designed for everyone who has passion for Data Science.

Curriculum

  • Module 1: From Problem to Approach
    • Business Understanding
    • Analytic Approach
  • Module 2: From Requirements to Collection
    • Data Requirements
    • Data Collection
  • Module 3: From Understanding to Preparation
    • Data Understanding
    • Data Preparation
  • Module 4: From Modeling to Evaluation
    • Modeling
    • Evaluation
  • Module 5: From Deployment to Feedback
    • Deployment
    • Feedback
  • Final Project

Tools you will learn in Data Science Methodology (DS0103EN) course:

  • Jupyter Notebook
  • R

FAQs

  • Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data,[1][2] and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.
  • Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyze actual phenomena" with data.[3] It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational, and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge.
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