Python for Data Analysis: Projects to Power Your Resume

Python for Data Analysis: Projects to Power Your Resume, available at $19.99, has an average rating of 4.4, with 68 lectures, 15 quizzes, based on 10 reviews, and has 75 subscribers.

You will learn about Complete hands-on projects analyzing real-world data, such as e-commerce sales and social media sentiments. Master basic Python syntax and data types, setting a strong foundation for advanced data analysis. Effectively manipulate and clean data using Pandas, preparing for real-world data analysis projects. Create powerful data visualizations with Matplotlib and Seaborn to derive insights from datasets. Understand and apply Python's advanced structures like lists, tuples, sets, and dictionaries in data analysis. Gain introductory knowledge in machine learning, focusing on applications in sentiment analysis. Develop a portfolio of practical Python projects, demonstrating skills to potential employers in data analysis. This course is ideal for individuals who are This course is for anyone who wants to kickstart their career in Data Analytics or This course is for anyone who wants to learn more about Python or This course is for anyone who wants to learn more about programming languages or This course is for anyone who wants to learn more about data visualizations or This course is for anyone who wants to create a portfolio of coding projects for their resume. It is particularly useful for This course is for anyone who wants to kickstart their career in Data Analytics or This course is for anyone who wants to learn more about Python or This course is for anyone who wants to learn more about programming languages or This course is for anyone who wants to learn more about data visualizations or This course is for anyone who wants to create a portfolio of coding projects for their resume.

Enroll now: Python for Data Analysis: Projects to Power Your Resume

Summary

Title: Python for Data Analysis: Projects to Power Your Resume

Price: $19.99

Average Rating: 4.4

Number of Lectures: 68

Number of Quizzes: 15

Number of Published Lectures: 68

Number of Published Quizzes: 15

Number of Curriculum Items: 83

Number of Published Curriculum Objects: 83

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Complete hands-on projects analyzing real-world data, such as e-commerce sales and social media sentiments.
Master basic Python syntax and data types, setting a strong foundation for advanced data analysis.
Effectively manipulate and clean data using Pandas, preparing for real-world data analysis projects.
Create powerful data visualizations with Matplotlib and Seaborn to derive insights from datasets.
Understand and apply Python's advanced structures like lists, tuples, sets, and dictionaries in data analysis.
Gain introductory knowledge in machine learning, focusing on applications in sentiment analysis.
Develop a portfolio of practical Python projects, demonstrating skills to potential employers in data analysis.

Who Should Attend

This course is for anyone who wants to kickstart their career in Data Analytics
This course is for anyone who wants to learn more about Python
This course is for anyone who wants to learn more about programming languages
This course is for anyone who wants to learn more about data visualizations
This course is for anyone who wants to create a portfolio of coding projects for their resume.

Target Audiences

This course is for anyone who wants to kickstart their career in Data Analytics
This course is for anyone who wants to learn more about Python
This course is for anyone who wants to learn more about programming languages
This course is for anyone who wants to learn more about data visualizations
This course is for anyone who wants to create a portfolio of coding projects for their resume.

Launch Your Data Analysis Journey with Real Python Projects!

Welcome to an exhilarating ride through the world of Python data analysis, where each line of code you write brings you closer to becoming a data wizard! Learning python can be hard, I’ve been there. I’ve designed this course so you learn in practically and complete 5 projects using real data. These projects will look GREAT on your resume!

Why Python? Python is not just a programming language; it’s a gateway to a universe of possibilities in data analysis, machine learning, and beyond. It’s versatile, user-friendly, and, most importantly, in high demand across industries!

My Unique Approach: Practical, Project-Based Learning

Practical and Hands-On: Forget about dull lectures! Dive head-first into coding exercises and real data challenges.
Project-Based Brilliance: Each module introduces a project tied to a real-world scenario, helping you build a portfolio that speaks louder than words.
Resume-Ready Projects: Walk away with a portfolio packed with projects like analyzing Amazon sales, dissecting e-commerce patterns, and even getting insights from social media data on trending topics like ChatGPT.
Real Data, Real Skills: Work with datasets from actual businesses, learning to clean, manipulate, and visualize data just like a pro data analyst.

What’s Inside the Course?

Python Basics: The ABCs of Python, including syntax, variables, and loops, to solidify your coding foundation.
Data Analysis Tools: Become a Pandas powerhouse and a maestro of data manipulation and cleaning.
Advanced Python Structures: Lists, tuples, sets, dictionaries – handle them all with finesse!
Data Visualization: Paint stories with data using Matplotlib and Seaborn.
Introduction to Machine Learning: Dip your toes into the future with sentiment analysis.
Comprehensive Curriculum: Covering everything from Python introduction to advanced data analysis techniques.
Interactive Coding Exercises: Cement your learning with engaging, hands-on coding challenges.

Who Is This Course For?

Aspiring data analysts looking to jumpstart their careers.
Python enthusiasts eager to apply their skills to real-world projects.
Anyone looking to add high-impact projects to their portfolio.
Career switchers aiming to break into the data science and analytics field.

Your Learning Journey

Each step on this journey equips you with critical skills. You’ll not just learn Python; you’ll think, analyze, and solve problems like a seasoned data analyst. And by the end of this course, you’ll have a portfolio that opens doors and a skill set that turns heads.

Enroll now and transform from Python learner to Python developer!

Course Curriculum

Chapter 1: Introduction to the Course and Installation

Lecture 1: Introduction to the Course

Lecture 2: Install Python and Anaconda on Windows

Lecture 3: Install Python and Anaconda on Mac

Lecture 4: Accessing the materials needed for the course

Chapter 2: Introduction to Spyder and Python

Lecture 1: Introduction to Spyder

Lecture 2: Basic Run Through of Python

Lecture 3: Basic Foundations of Python

Chapter 3: Introduction to Numpy

Lecture 1: Introduction to Numpy

Lecture 2: Calculating Statistics with Numpy

Lecture 3: Indexing and Slicing with Numpy

Chapter 4: Introduction to Pandas

Lecture 1: Introduction to Pandas

Lecture 2: Accessing Data in a DataFrame

Lecture 3: Grouping and Aggregating Data with DataFrames

Lecture 4: How to Merge DataFrames

Chapter 5: Project 1 Analyzing Amazon Sales Data

Lecture 1: Analyzing Amazon Sales Data – Introduction

Lecture 2: Importing, Exploring and Cleaning Data

Lecture 3: Aggregating Sales Data

Lecture 4: Renaming Columns and Exporting Data

Lecture 5: Uploading code to Github

Chapter 6: Project 2 Analyzing E-commerce Orders

Lecture 1: Analyzing E-commerce Orders – Introduction

Lecture 2: Setting the Working Directory in Python

Lecture 3: Loading Data Files and Checking Data Quality

Lecture 4: Handling Missing Values in Python

Lecture 5: Checking for Duplicate Data

Lecture 6: Filtering Data on Python

Lecture 7: Merging and Joining DataFrames

Lecture 8: Creating Data Visualizations

Lecture 9: Editing and Customizing Plots in Python

Lecture 10: Creating a Scatter Plot

Lecture 11: Creating a Stacked Bar Chart

Lecture 12: Creating Boxplots on Python

Lecture 13: Creating Subplots in Python

Chapter 7: Project 3 Analyzing Pizza Sales

Lecture 1: Analyzing Pizza Sales and Importing Data

Lecture 2: Exploring Data Frames and Descriptive Statistics

Lecture 3: Dealing with Rows and Columns in Pandas

Lecture 4: Understanding Indexing in DataFrames

Lecture 5: Truncating DataFrames and Series in Python

Lecture 6: Filtering DataFrames

Lecture 7: Working with missing data

Lecture 8: Deleting specific rows and columns in a DataFrame

Lecture 9: Sorting DataFrames

Lecture 10: Grouping on Python

Lecture 11: Merging and Concatenating in Python

Lecture 12: Changing cases in Python

Lecture 13: Replacing text in Dataframe Columns

Lecture 14: Removing Whitespaces from Columns

Lecture 15: Generating a boxplot

Lecture 16: Project Closeoff

Chapter 8: Project 4 Loan Analysis Overview

Lecture 1: Loan Analysis Overview – Introduction

Lecture 2: Importing Data on Python

Lecture 3: Joining Data on Python

Lecture 4: Steps to clean data in Python

Lecture 5: Introduction to Functions in Python

Lecture 6: Creating a Function on the Loan Dataset

Lecture 7: Conditional Statements on Python

Lecture 8: Practical Application of Functions and Conditions

Lecture 9: Working with Conditional Statements and Averages in Functions

Lecture 10: Classes in Python

Lecture 11: Data Visualizations on Python

Lecture 12: Quick Overview of Subplots in Python

Chapter 9: Project 5 Sentiment Analysis

Lecture 1: Sentiment Analysis – Introduction

Lecture 2: Loading and Reviewing Data

Lecture 3: Detecting Languages and using try and except

Lecture 4: Cleaning Text Data

Lecture 5: Developing a sentiment function

Lecture 6: Creating a Wordcloud

Lecture 7: Creating a countplot for sentiment

Chapter 10: Conclusion

Lecture 1: Conclusion

Instructors

Dee Naidoo
Data Engineer, Tableau Enthusiast, Data Analyst, Python Dev

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4 stars: 3 votes
5 stars: 5 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!

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