13 h26 ita     rick and morty 2025     zom 100     geordie shore s25e08     Annette Focks     dillion harper     1977     peen     1977     running the sahara     free willy     ted s01     1977     battle angel     11 11     Hololive idol project rid     ableton     demon slayer     1977     homegrown-terror    

Udemy - Python for Data Analysts - The Complete Flagship

seeders: 2
leechers: 19
Added 12 hours ago by freecoursewb in Other

Download Fast Safe Anonymous
movies, software, shows...

Files

Udemy - Python for Data Analysts - The Complete Flagship (Size: 2.9 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Why Python, Why Now (The Analyst's Turning Point)
  1. The Day Excel Broke.mp4 35.3 MB
  10 - Pandas IV Time Series for Analysts
  11 - Pandas V Performance & When to Reach Further
  12 - Data Visualization I Matplotlib Foundations
  13 - Data Visualization II Seaborn & Statistical Plots
  14 - Data Visualization III Interactive & Dashboards
  15 - Data Storytelling & Presentation
  16 - Excel + Python Bridging the Two Worlds
  17 - SQL + Python Databases Without Manual Exports
  18 - APIs & Web Data
  19 - Statistics for Analysts I Foundations
  2 - Python Fundamentals I Variables, Types, Logic
  20 - Statistics for Analysts II Inference & Testing
  21 - Light ML & Forecasting for Analysts
  22 - AI-Augmented Analytics for Analysts
  23 - Automation & Scheduling
  24 - Working with Bigger Data
  25 - Tooling, Git & Reproducibility
  26 - Recap & Bridge
  27 - Case Studies Real Company-Shaped Problems
  28 - BI Integration
  29 - Career & Interview Playbook
  3 - Python Fundamentals II Functions & Robustness
  10. Error Handling.mp4 32.8 MB
  11. Modules & Imports.mp4 34 MB
  12. Debugging Muscle.mp4 2.7 MB
  30 - Capstone End-to-End Analyst Project
  31 - Module Quizzes (Optional Review)
  1. Module 1 Check Why Python, Why Now.html 25.3 KB
  10. Module 10 Check Pandas IV Time Series for Analysts.html 27.6 KB
  11. Module 11 Check Pandas V Performance & When to Reach Further.html 28.5 KB
  12. Module 12 Check Data Visualization I Matplotlib Foundations.html 27.3 KB
  13. Module 13 Check Data Visualization II Seaborn & Statistical Plots.html 25.4 KB
  14. Module 14 Check Data Visualization III Interactive & Dashboards.html 24.8 KB
  15. Module 15 Check Data Storytelling & Presentation.html 24.8 KB
  16. Module 16 Check Excel + Python Bridging the Two Worlds.html 25.3 KB
  17. Module 17 Check SQL + Python Databases Without Manual Exports.html 25.3 KB
  18. Module 18 Check APIs & Web Data.html 25.1 KB
  19. Module 19 Check Statistics for Analysts I Foundations.html 27.1 KB
  2. Module 2 Check Python Fundamentals I Variables, Types, Logic.html 24.1 KB
  20. Module 20 Check Statistics for Analysts II Inference & Testing.html 27.3 KB
  21. Module 21 Check Light ML & Forecasting for Analysts.html 28.4 KB
  22. Module 22 Check AI-Augmented Analytics for Analysts.html 27.5 KB
  23. Module 23 Check Automation & Scheduling.html 26.5 KB
  24. Module 24 Check Working with Bigger Data.html 27.7 KB
  25. Module 25 Check Tooling, Git & Reproducibility.html 26.3 KB
  26. Module 26 Check Recap & Bridge.html 25.3 KB
  27. Module 27 Check Case Studies Real Company-Shaped Problems.html 27.1 KB
  28. Module 28 Check BI Integration.html 26.4 KB
  29. Module 29 Check Career & Interview Playbook.html 26.5 KB
  3. Module 3 Check Python Fundamentals II Functions & Robustness.html 25.5 KB
  30. Module 30 Check Capstone End-to-End Analyst Project.html 27.8 KB
  4 - Data Structures Every Analyst Needs
  13. Lists & Tuples.mp4 9 MB
  14. Dictionaries & Sets.mp4 27.2 MB
  15. Comprehensions.mp4 24.7 MB
  16. Lambda, map() & filter().mp4 6.4 MB
  17. Nested Structures.mp4 38.6 MB
  5 - Files & Formats Reading the Real World
  18. CSV the Right Way.mp4 35.1 MB
  19. Excel Files in Python.mp4 31.9 MB
  20. JSON & Parquet.mp4 40.8 MB
  6 - NumPy Foundations (Just Enough)
  21. Arrays & Vectorization.mp4 32.6 MB
  22. NumPy Anti-Patterns.mp4 33.7 MB
  7 - Pandas I Series & DataFrame Fundamentals
  23. Your First DataFrame.mp4 16.1 MB
  24. Selecting & Filtering.mp4 14.7 MB
  25. Sorting & Ranking.mp4 12.6 MB
  26. MultiIndex.mp4 29.2 MB
  8 - Pandas II Cleaning Real Data + Systematic EDA
  27. Missing Data.mp4 25.5 MB
  28. Dtypes & Conversion.mp4 14.1 MB
  29. String Cleaning.mp4 13.8 MB
  30. Working with Text Data.mp4 28.2 MB
  31. Your First Look at a Dataset.mp4 15.5 MB
  32. Automated Profiling Tools.mp4 14.8 MB
  33. Duplicates & Validation.mp4 36.2 MB
  9 - Pandas III Reshaping & Combining
  34. GroupBy The Pattern That Replaces Every Excel Pivot Table.mp4 38 MB
  35. Pivot Tables & Melt Reshaping Between Wide and Long.mp4 17 MB
  36. Merge & Join Why Do I Suddenly Have More Rows.mp4 16.9 MB
  37. Concatenation Twelve Monthly CSVs Into One DataFrame.mp4 31 MB
  4. Module 4 Check Data Structures Every Analyst Needs.html 25.3 KB
  5. Module 5 Check Files & Formats Reading the Real World.html 25.3 KB
  6. Module 6 Check NumPy Foundations (Just Enough).html 25.2 KB
  7. Module 7 Check Pandas I Series & DataFrame Fundamentals.html 27.5 KB
  8. Module 8 Check Pandas II Cleaning Real Data + Systematic EDA.html 27.7 KB
  9. Module 9 Check Pandas III Reshaping & Combining.html 27.6 KB
  95. Build Walkthrough Part 2.mp4 52 MB
  96. Build Walkthrough Part 3.mp4 45.7 MB
  97. Capstone Brief.mp4 36.3 MB
  98. Build Walkthrough Part 1.mp4 50.4 MB
  9. Functions.mp4 39.8 MB
  92. The Analyst Interview.mp4 38.8 MB
  93. Building a Portfolio Project.mp4 37.4 MB
  94. Career Framing.mp4 29.6 MB
  90. Feeding Power BI Tableau from Python.mp4 46.3 MB
  91. Building a Self-Serve Streamlit App.mp4 32.7 MB
  86. Marketing Analytics.mp4 35.7 MB
  87. Finance Ops Reporting.mp4 36.2 MB
  88. E-commerce Funnel Analysis.mp4 36.7 MB
  89. Product Analytics.mp4 52.6 MB
  85. The Analyst's Toolkit So Far.mp4 47.3 MB
  82. Virtual Environments & Package Management.mp4 30.4 MB
  83. Git Basics for Analysts.mp4 29.4 MB
  84. Notebook Hygiene & Testing.mp4 35.8 MB
  80. Chunked Reading.mp4 38.8 MB
  81. DuckDB for Analysts.mp4 37.9 MB
  77. Writing a Script, Not a Notebook.mp4 19.4 MB
  78. Scheduling.mp4 34.8 MB
  79. Emailing Reports.mp4 35.5 MB
  72. LLMs as Your Python Co-Pilot.mp4 19.6 MB
  73. AI-Assisted Debugging.mp4 20.8 MB
  74. Prompt Engineering for Data Tasks.mp4 10.6 MB
  75. Copilot in Jupyter VS Code.mp4 8.7 MB
  76. The AI Analyst Workflow.mp4 31.5 MB
  68. When ML Is (and Isn't) the Right Tool.mp4 34.8 MB
  69. Scikit-Learn Basics Train, Predict, and Not Fool Yourself.mp4 30.6 MB
  70. Forecasting Sales and Demand Trend, Seasonality, and a Real Range.mp4 18 MB
  71. Classification for Analysts Churn, Conversion, and the Accuracy Trap.mp4 37.9 MB
  65. Hypothesis Testing t-tests, Chi-Square, and the P-Value Trap.mp4 43.1 MB
  66. A B Testing in Practice The Checkout Button Test.mp4 30.8 MB
  67. Correlation & Simple Regression Correlation Is Not Causation.mp4 31.1 MB
  4. Variables & Data Types.mp4 29.1 MB
  5. Operators & Expressions.mp4 32.3 MB
  6. Control Flow.mp4 29.3 MB
  7. Loops.mp4 35.3 MB
  8. Jupyter Magic Commands.mp4 28.3 MB
  62. Descriptive Statistics Why the Average Salary Lies.mp4 17.4 MB
  63. Distributions Why Wait Times Never Look Like a Bell Curve.mp4 30.1 MB
  64. Sampling & Confidence Intervals The Assumption Every KPI Hides.mp4 37.3 MB
  59. HTTP & requests Fundamentals.mp4 19.1 MB
  60. Working with REST APIs.mp4 37.8 MB
  61. Web Scraping Basics & Ethics.mp4 30.2 MB
  56. Connecting to a Database.mp4 37.3 MB
  57. Writing Back.mp4 31.1 MB
  58. SQL vs Pandas.mp4 26.3 MB
  53. Reading Writing Excel at Scale.mp4 43.2 MB
  54. xlwings — Driving Excel from Python.mp4 18.2 MB
  55. Replacing Fragile Workbooks.mp4 52.8 MB
  50. The 'So What' Framework.mp4 33.2 MB
  51. Chart Annotation for Non-Technical Audiences.mp4 34.9 MB
  52. Choosing the Right Chart for the Message.mp4 34.5 MB
  48. Plotly for Interactivity.mp4 23.8 MB
  49. Streamlit Micro-Dashboards.mp4 18.8 MB
  46. Distributions & Relationships.mp4 25.5 MB
  47. Categorical Comparisons & Heatmaps.mp4 25 MB
  44. The Grammar of a Chart.mp4 41 MB
  45. Formatting for Humans.mp4 46.6 MB
  41. Vectorize, Don't Iterate.mp4 52.3 MB
  42. Memory & Chunking.mp4 9.2 MB
  43. Polars & DuckDB -- When Pandas Isn't Enough.mp4 35.4 MB
  38. Dates & Times.mp4 43.2 MB
  39. Resampling & Rolling Windows.mp4 9.3 MB
  40. Time-Based Analysis Patterns.mp4 46.4 MB
  2. Get Running in 10 Minutes.mp4 30.3 MB
  3. Thinking Like a Programmer.mp4 37 MB

Description


Python for Data Analysts: The Complete Flagship
https://WebToolTip.com
Published 7/2026

Created by Snowbrix Academy

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: Beginner | Genre: eLearning | Language: English | Duration: 98 Lectures ( 10h 15m ) | Size: 3 GB
From your first line of Python to pandas, SQL, stats, ML, AI-augmented workflows, and a real capstone.
What you'll learn

⚡ Write real, idiomatic Python — control flow, functions, data structures, comprehensions, error handling — without copy-pasting from Stack Overflow

⚡ Clean, reshape, merge, and time-index messy real-world data in pandas at production quality, not toy-CSV quality

⚡ Replace slow, fragile Excel workflows with short, reproducible Python scripts

⚡ Pull data directly from SQL databases and REST APIs into pandas instead of manual exports

⚡ Produce publication-quality static charts and interactive dashboards, and tell a clear story with them

⚡ Apply correct statistical reasoning — distributions, hypothesis tests, A/B tests, regression — avoiding the most common analyst-level mistakes

⚡ Build and interpret a basic forecasting/classification model with scikit-learn, and know when NOT to reach for ML

⚡ Use AI tools (ChatGPT/Claude/Copilot) as a Python co-pilot while retaining independent analytical judgment

⚡ Automate a recurring report end-to-end: pull, clean, analyze, chart, schedule, deliver

⚡ Work with performance-conscious pandas, and know when to reach for Polars/DuckDB, so a multi-million-row file doesn't crash a laptop

⚡ Talk about all of the above in an analytics interview the way a senior analyst does — trade-offs, not just syntax
Requirements

❗ No programming experience required — this course starts from your very first line of Python

❗ Basic spreadsheet/Excel familiarity is helpful (we translate concepts directly from Excel) but not required

❗ A computer with an internet connection — Google Colab (used throughout) needs nothing installed

❗ No cost: Python, Colab, Anaconda, and every library used in this course are free and open-source

❗ Curiosity about your own data — bring a real spreadsheet or dataset from your job if you have one

Related Torrents

torrent name size uploader age seed leech
19
0
21
0
0