Data Science 101- Python Plus Excel

Data Science 101: Python Plus Excel, available at $54.99, has an average rating of 5, with 82 lectures, based on 2 reviews, and has 102 subscribers.

You will learn about Write excel advanced conditional, text, and lookup functions Excel automation using python Learn Microsoft Excel 2016 and many of its advanced features Learn data science skills using Python and Excel Excel features using numpy and pandas Visualization using Excel and Python This course is ideal for individuals who are Excel users curious about automating their work using python or Python Developer wanting career switch in Data Science It is particularly useful for Excel users curious about automating their work using python or Python Developer wanting career switch in Data Science.

Enroll now: Data Science 101: Python Plus Excel

Summary

Title: Data Science 101: Python Plus Excel

Price: $54.99

Average Rating: 5

Number of Lectures: 82

Number of Published Lectures: 82

Number of Curriculum Items: 82

Number of Published Curriculum Objects: 82

Original Price: $149.99

Quality Status: approved

Status: Live

What You Will Learn

Write excel advanced conditional, text, and lookup functions

Excel automation using python

Learn Microsoft Excel 2016 and many of its advanced features

Learn data science skills using Python and Excel

Excel features using numpy and pandas

Visualization using Excel and Python

Who Should Attend

Excel users curious about automating their work using python

Python Developer wanting career switch in Data Science

Target Audiences

Excel users curious about automating their work using python

Python Developer wanting career switch in Data Science

For many years, and for good reason, Excel has been a staple for working professionals. It is essential in all facets of business, education, finance, and research due to its extensive capabilities and simplicity of use.

Over the past few years, python programming language has become more popular. According to one study, the demand for Python expertise has grown by 27.6 %over the past year and shows no indications of slowing down. Python has been a pioneer in web development, data analysis, and infrastructure management since it was first developed as a tool to construct scripts that “automate the boring stuff.”

Why python is important for automation?

Consider being required to create accounts on a website for 10,000 employees. What do you think? Performing this operation manually and frequently will eventually drive you crazy. It will also take too long, which is not a good idea.

Try to consider what it’s like for data entry workers. They take the data from tables (like those in Excel or Google Sheets) and insert it elsewhere.

They read various magazines and websites, get the data there, and then enter it into the database. Additionally, they must perform the calculations for the entries.

In general, this job’s performance determines how much money is made. Greater entry volume, more pay (of course, everyone wants a higher salary in their job).

However, don’t you find doing the same thing over and over boring?

The question is now, “How can I accomplish it quickly?”

How to automate my work?

Spend an hour coding and automating these kinds of chores to make your life simpler rather than performing these kinds of things by hand. By just writing fewer lines of Python code, you can automate your strenuous activity.

The course covers following topics:

1. Excel basics

2. Excel Functions

3. Excel Visualizations

4. Excel Case study (Financial Statements)

5. Python numpy and pandas

6. Python Implementations of Excel functions

7. Python matplotlib and pandas visualizations

The evidence suggests that both Excel and Python have their place with certain applications. Excel is a great entry-level tool and is a quick-and-easy way to analyze a dataset.

But for the modern era, with large datasets and more complex analytics and automation, Python provides the tools, techniques and processing power that Excel, in many instances, lacks. After all, Python is more powerful, faster, capable of better data analysis and it benefits from a more inclusive, collaborative support system.

Python is a must-have skill for aspiring data analysts, data scientist and anyone in the field of science, and now is the time to learn.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Python vs Excel

Lecture 3: Limitation of Excel

Lecture 4: Python

Lecture 5: who can benefit from learning Python?

Lecture 6: What makes Python a better option than Excel?

Lecture 7: Excel vs Python: Who wins?

Chapter 2: Download Resources for Excel [IMPORTANT]

Lecture 1: Download Excel Lecture content!

Chapter 3: Introduction to Basics of Excel

Lecture 1: Structure of Excel sheets

Lecture 2: The Ribbon

Lecture 3: Rows and Columns

Lecture 4: Enter, Edit, Delete in Excel

Lecture 5: Excel basic formatting: border, font, color

Lecture 6: Align Left, Right, Center

Lecture 7: Arithmetic operations

Lecture 8: Excel formulas introduction

Lecture 9: Copy and Paste

Lecture 10: Formatting cell

Lecture 11: Formatting worksheet

Lecture 12: Moving and selecting contents in Excel sheets

Lecture 13: [IMPORTANT] Fixing cell references

Lecture 14: ALT+ENTER

Lecture 15: Text to Column

Lecture 16: Wrap Text

Lecture 17: Select special

Lecture 18: Dynamic Naming

Lecture 19: Custom Formatting 1

Lecture 20: Custom Formatting 2

Lecture 21: Multiple Formats

Chapter 4: Excel Tools and Tips

Lecture 1: Macros

Lecture 2: Data Validation

Lecture 3: Sort and Filter

Lecture 4: Hyperlinks

Lecture 5: Freeze Panes

Lecture 6: Tell me what you want to do

Lecture 7: Keyboard Shortcuts

Chapter 5: Excel Functions

Lecture 1: Count, countif and countifs

Lecture 2: Sum, sumif and sumifs

Lecture 3: average and averageif

Lecture 4: Text functions

Lecture 5: max and min functions

Lecture 6: round function

Lecture 7: vlookup function [IMPORTANT}

Lecture 8: hlookup function

Lecture 9: index and match function

Lecture 10: iferror function

Lecture 11: pivot tables

Lecture 12: data tables

Chapter 6: Excel Visualizations

Lecture 1: Excel charts

Lecture 2: Basic formatting for charts

Lecture 3: Designing charts

Lecture 4: Bridge charts

Lecture 5: Treemap

Lecture 6: Spark Lines

Chapter 7: Excel Case Study

Lecture 1: Introduction to data

Lecture 2: Preprocessing data

Lecture 3: Create unique code (primary key)

Lecture 4: Creating database

Lecture 5: Populate database 1

Lecture 6: Populate database 2

Lecture 7: Mapping each row to category

Lecture 8: Income statement

Lecture 9: Format statement

Lecture 10: Format statement more

Lecture 11: Populate Income (P&L) statement

Chapter 8: Excel Functions in Python

Lecture 1: vlookup function in excel

Lecture 2: Implement vlookup functionality in Python

Lecture 3: Pivot tables in excel

Lecture 4: Implement pivot tables functionality in Python

Lecture 5: Pivot tables using pandas

Lecture 6: IF function in Excel

Lecture 7: IF functionalities in python

Lecture 8: Text manipulation in Excel

Lecture 9: Text manipulation in Python

Lecture 10: count, countif, countifs, sum, sumif, sumifs

Lecture 11: count, countif, countifs, sum, sumif, sumifs in Python

Chapter 9: Python Visualizations

Lecture 1: pivot charts in Excel

Lecture 2: Python pandas visualization

Lecture 3: Matplotlib

Lecture 4: Formatting charts

Lecture 5: More on matplotlib

Lecture 6: matplotlib and pandas together

Instructors

Sachin Kafle
Founder of CSAMIN & Bit4Stack Tech Inc. [[Author, Teacher]]

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5 stars: 2 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!