Data Science

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About Course

Data Science is one of the best-suited professions to thrive this century. It is digital, programming-oriented, and analytical. Therefore, it comes as no surprise that the demand for data scientists has been surging in the job marketplace.

However, supply has been very limited. It is difficult to acquire the skills necessary to be hired as a data scientist.

Who this course is for:

  1. You should take this course if you want to become a Data Science or if you want to learn about the field
  2. This course is for you if you want a great career
  3. The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
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What Will You Learn?

  • Learn the basics of Data Science

Course Content

Data Science

  • Introduction to Data Science – Fundamental Concepts
    00:00
  • Data Wrangling: Part 1esson
    00:00
  • Data Wrangling: Part 2n
    00:00
  • Data Wrangling: Part 3
    00:00
  • Data Wrangling: Part 4 – SQL
    00:00
  • Data Wrangling: Part 5 – Trends in Database Systems
    00:00
  • Data Wrangling: Part 6 – Data Processing Using Python
    00:00
  • Data Science Experiments using Hypothesis Testing: Part 1
    00:00
  • Data Science Experiments using Hypothesis Testing : Part 2
    00:00
  • Data Science Experiments using Hypothesis Testing: Part 3 – A/B Testing
    00:00
  • Data Science Experiments using Hypothesis Testing: Part 4
    00:00
  • Data Science Experiments using Hypothesis Testing: Part 5
    00:00
  • Data Science Experiments using Hypothesis Testing: Part 6
    00:00
  • Supervised Learning: Linear Regression – Part 1
    00:00
  • Supervised Learning: Linear Regression – Part 2
    00:00
  • Supervised Learning: Linear Regression – Part 3
    00:00
  • Supervised Learning: Linear Regression – Part 4
    00:00
  • Supervised Learning: Example using Python – Part 5
    00:00
  • Supervised Learning: Example using Python – Part 6
    00:00
  • Logistic Regression: Part 1
    00:00
  • Logistic Regression: Part 2
    00:00
  • Back Propagation
    00:00

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