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1

Successful Students

2 hours

Course length

1

Enrollments

Course Language

English

Course Description

In this course of machine learning for data analysis, you will experience the life cycle of data exploration to build ML learning model, resembling the work of a data scientist. You will learn about supervised and unsupervised machine learning with industry use cases and practical examples using Jupyter notebooks.

Course Goals

In this course of machine learning for data analysis, you will be able to understand machine learning, various machine learning algorithms, practical use cases from banking and telecom industry, five steps of exploratory data analysis and walk through of Python code using Jupyter notebooks.

Audience

This course of machine learning is of intermediate level in terms of complexity and useful for those who want to take next level in their data science career. If you are beginner who wants to kick start their journey to become data scientist, check out data science foundation course and python course on edilume

Topics Covered

In this course of machine learning for data analysis, we will cover following topics

  • Introduction to machine learning
  • Exploratory data analysis (EDA)
  • EDA - Data description
  • EDA - Graphical Analysis of data
  • EDA - Data Cleaning
  • Model Building
  • Rule of Model Building
  • Churn Prediction Use Case
  • Supervised Learning - Banking Loan Use Case
  • Supervised Learning - Regression
  • Unsupervised Learning - Clustering
  • Jupyter notebook review on supervised and unsupervised learning use cases

  • Requirements

    Before taking this course of machine learning for data analysis, it is good to take data science foundation course on edilume. In addition, basic working experience with data analysis and using python is recommended. Here is a basic python foundation course to get you started.

    Instructor

    Sana Salman has been working in Data science domain for the last 15 years. She has initiated and built data science pipelines in telecom, financial sectors, health and retail. She is a Fulbright scholar and did my MS from WPI, USA. She is currently doing her Doctoral with Macquarie University, Sydney. You can reach her via her LinkedIn profile at Sana Salman

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    What you will get upon completion

    In this course of machine learning for data analysis, you will get advanced working knowledge on the use of Machine Learning for performing data analysis using Python. After course completion, you can also get a course certificate that you can show to your prospective or current employer to demonstrate your proof of competency and skill on this subject.

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