Advancing into Data Analytics from Excel to Python
- Created By raju2006
- Last Updated August 26th, 2023
- Overview
- Curriculum
- FAQs
Description:
Excel users will review the foundations of data analytics using Excel and then transfer and advance that knowledge to perform a complete data analysis using the Python programming language. You will learn how to conduct exploratory data analysis, data visualization and hypothesis testing, and you’ll learn how to use Python to access and manipulate Excel files. At the end of the course, you will be able to perform a complete data analysis using Python.
Course Code/Duration:
BDT117 / 1 Day
Pre-requisite:
- Basic Programming &Excel knowledge
Audience:
This session is designed for software developers, software architects, network engineers, system operators managing cloud.
Learning Objectives:
After this course, you will be able to:
- Understand the Foundations of Analytics in Excel
- Explore Variables in Excel
- Understand Exploratory Data Analysis
- Understand the Foundations of Inferential Statistics and Hypothesis Testing
- Use the Python Programming Language for Data Analysis
- Access Excel Files Using Python
- Perform Data Visualization and Exploration in Python
- Perform More Efficient and Deeper Data Analyses using Python
- Explore Correlation and Linear Regression in Excel and Python
- Use Python to Manipulate Excel Files
- Use Python to Perform Machine Learning
Topic Outline:
Overview of Data Analytics
Excel Review
- Foundations of Analytics in Excel
- Variables in Excel
- Exploratory Data Analysis in Excel
- Data Visualization in Excel
Introduction to the Python Programming Language
- Installing Anaconda
Milestone 1: Learn how to use Jupyter Notebooks
- Python Essentials
- Introduction to Pandas
- Using Pandas to access Excel files
- Data Analysis with Pandas
Milestone 2: Perform exploratory data analysis using Pandas
- Using Python for data wrangling
- Using Python to manipulate Excel files
- Data Visualization in Python
- Matplotlib
- Pandas
- Seaborn
Milestone 3: Perform data visualization using Python
- Inferential Statistics and Hypothesis Testing in Python
- Correlation and Linear Regression using Excel and Python
- Using Python to perform machine learning
Milestone 4: Perform complete Python data analysis
- Conclusion: Data Analytics in the real world, next steps.
Structured Activity/Exercises/Case Studies:
- Milestone 1: Learn how to use Jupyter Notebooks
- Milestone 2: Perform exploratory data analysis using Pandas
- Milestone 3: Perform data visualization using Python
- Milestone 4: Perform complete Python data analysis
Training material provided:
Yes (Digital format)
Can I Just Enroll In A Single Course?
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How Much Do I Have To Pay For Unreal Engine?
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What Background Knowledge Is Necessary?u2029
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What Is The Refund Policy?
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The curriculum is empty
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