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Python for Data Analytics - Full Course for Beginners

Luke Barousse 618,236 lượt xem 10 months ago
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🧮 Course Problems & Certificate 👉 https://lukeb.co/python
📝 Course Code & Notes 👉 https://lukeb.co/python_repo

My FREE Course to be a Data Analyst 👉 https://lukebarousse.com/5daycourse

Connect with Kelly Adams, the course producer:
👩🏻‍💼 Kelly’s LinkedIn: https://www.linkedin.com/in/kellyjianadams
🌐 Kelly’s Website: https://www.kellyjadams.com

0️⃣ Course Intro
==============
0:00:00 - Welcome
0:03:12 - What is Python?
0:04:51 - Intro to Course

1️⃣ Basics Chapter
==============
0:08:42 - Getting Started
0:18:52 - Variables
0:24:25 - Python Terms
0:38:06 - Data Types
0:48:41 - Strings
1:02:04 - ChatBot Help
1:05:06 - String Formatting
1:15:10 - Operators Part 1
1:26:20 - Conditional Statements
1:34:24 - Lists
1:49:42 - Dictionaries
1:59:54 - Sets
2:05:15 - Tuples
2:12:26 - Operators Part 2
2:21:06 - Loops
2:36:31 - List Comprehensions
2:44:16 - Exercise: Basics
2:52:12 - Functions
3:02:03 - Lambda
3:12:46 - Modules
3:28:16 - Exercise: Python Library
3:40:05 - Library
3:52:33 - Classes
4:10:44 - NumPy: Intro
4:22:56 - Pandas: Intro
4:33:09 - Pandas: Inspection
4:47:20 - Pandas: Cleaning
4:58:46 - Pandas: Analysis
5:08:26 - Exercise: Pandas Basics
5:17:19 - Matplotlib: Intro
5:21:23 - Matplotlib: Plotting
5:34:41 - Matplotlib: Labeling
5:40:34 - Matplotlib: Pandas Plotting
5:46:00 - Exercise: Matplotlib Basics

2️⃣ Advanced Chapter
================
5:50:56 - Python Install (Anaconda)
6:00:34 - VS Code Install
6:10:49 - Virtual Environments (See Pinned Comment)
6:27:15 - Pandas: Accessing Data
6:35:38 - Pandas: Data Cleaning
6:42:54 - Pandas: Data Management
6:49:35 - Pandas: Pivot Tables
6:57:00 - Pandas: Index Management
7:04:50 - Exercise: Job Demand
7:15:37 - Pandas: Merge DataFrames
7:25:53 - Pandas: Concat DataFrames
7:34:31 - Pandas: Exporting Data
7:40:56 - Pandas: Applying Functions
7:56:39 - Pandas: Explode
8:08:27 - Exercise: Trending Skills
8:17:21 - Matplotlib: Format Charts
8:30:06 - Matplotlib: Pie Plots
8:40:04 - Matplotlib: Scatter Plots
8:50:35 - Matplotlib: Advanced Customization
9:06:00 - Matplotlib: Histograms
9:10:36 - Matplotlib: Box Plots
9:22:01 - Exercise: Skill Pay Analysis
9:31:39 - Seaborn: Intro

3️⃣ Project Chapter
===============
9:45:40 - Project: Intro
9:56:23 - Git & GitHub Setup
10:09:50 - Skill Demand
10:29:33 - Skills Trend
10:42:30 - Salary Analysis
10:50:57 - Optimal Skills
11:03:22 - Share on GitHub
11:06:04 - Share on LinkedIn

🔗 Links Mentioned
===============
1️⃣ Basics Links
- Dataset (Hugging Face) - https://huggingface.co/datasets/lukebarousse/data_jobs
- Functions Python Docs - https://docs.python.org/3/library/functions.html
- Python Standard Library - https://docs.python.org/3/library/index.html
- DateTime Docs - https://docs.python.org/3/library/datetime.html
- AST Docs - https://docs.python.org/3/library/ast.html
- Format String Literals - https://docs.python.org/3/reference/lexical_analysis.html#formatted-string-literals
- Pandas Docs - https://pandas.pydata.org/pandas-docs/stable/reference/index.html
- Matplotlib Docs - http://matplotlib.org/
- Matplotlib CheatSheet - https://matplotlib.org/cheatsheets/

2️⃣ Advanced Links
- VS Code Install - https://code.visualstudio.com/download
- Anaconda Install - https://anaconda.com/download/success
- Anaconda Docs - https://docs.conda.io
- Software Jobs CSV - https://lukeb.co/software_csv
- Joins Explained (SQL for Data Analytics) - https://lukeb.co/sql_joins
- Pandas Cheat Sheet - https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
- Seaborn Docs - https://seaborn.pydata.org/

3️⃣ Project Links
- Git Download - https://git-scm.com/downloads
- GitHub Signup - http://github.com/signup
- Markdown CheatSheet - https://www.markdownguide.org/cheat-sheet/

Social Media / Contact Me
======================
📫Newsletter: https://www.lukebarousse.com/
👨🏼‍💼 Linkedin: https://www.linkedin.com/in/luke-b/
🅧 X/Twitter: https://twitter.com/LukeBarousse
🌄 Instagram: https://www.instagram.com/lukebarousse/
⏰ TikTok: https://www.tiktok.com/@lukebarousse

As an Amazon, Coursera, and Parallels Affiliate Programs member, I earn a commission from qualifying purchases on the links above. It costs you nothing but helps me with content creation.

#datanerd #dataanalyst #datascience

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