Course Objectives:
- ‘Data Scientist’ has been ranked the number one job on Glassdoor all over the world, and is a highly employable sector.
- Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems.
- This course is designed for both, beginners with some programming experience, and experienced developers who want to upgrade their career into data analysis and visualization.
- By pursuing a course, you can enter the versatile field of data science because it is widely used in health-care, banking, consultancy services, and e-commerce industries, among others.
- This course enables you to become a well-trained engineer with hands-on training of in demand market skills.
Certification
Certification in Data Visualization and Analysis
Learning Outcomes
- Develop an understanding of how to program in Python
- Learn to create and manipulate arrays using Numpy and Python
- The course will teach you how to use pandas to create and analyze data sets
- Learn to use Matplotlib and Seaborn libraries to create beautiful data visualization
- Add value to your portfolio by learning Python Data Analysis Skills
- Get hands-on experience of creating a visualization of real-life projects
Course Eligibility
Students with any of the following qualifications will be considered as an eligible candidate for the course offered:
- Diploma / Degree / ME Graduated or Appearing
- Students from Mechanical / Electrical / Electronics and Telecommunication / Instrumentation / Mechatronics and Computers Streams
- B.Sc. and M.Sc. students from technical steam like Electronics and Instrumentation
Course Features
- Lectures 44
- Quizzes 0
- Duration 4 weeks
- Language English
- Students 15
- Assessments Yes
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Week 1
- Introduction
- Getting Started With Anaconda Distribution
- Introduction to Jupiter
- Pandas Introduction
- Project on Pandas
- Pivot Tables in Pandas
- Cross Tables in Pandas
- Comparison between Pivot and Cross tables
- Seaborn Project Introduction
- Seaborn Introduction
- Get Started with the Data
- Introduction to Univariate Plots
- Univariate Plots Practical Exercise
- Introduction to Bivariate Plots
- Multi Variate Plots in Seaborn
- Regression Plots In Seaborn
- Categorical Plots in Seaborn
- Seaborn Project
- Facet Grids in Seaborn
- Facet Grids Practical Exercise
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Week 2
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Week 3
- Project Introduction
- Loading Data
- Exploring the Data
- Cleaning the Data
- Correlation and Frequency Analysis
- Data Analysis with Group By Method
- Data Analysis and Visualization with Pivot Table
- ata Analysis & Visualization with Cross Table
- Project Finalization
- Plotly Introduction
- Plotly Project: World Development Indicators
- Install and Load Plotly and Data
- Pie Charts In Plotly
- Bar and Scatter in Plotly
- Animation Plots in Plotly
- Choropleth in Plotly
- Plotly Project Wrap Up
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Week 4
