| 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 |
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
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| 707.7 MB | freecoursewb | 12 hours | 26 | 19 | |
| 484.9 MB | freecoursewb | 12 hours | 0 | 0 | |
| 3.1 GB | freecoursewb | 12 hours | 22 | 21 | |
| 3.4 GB | freecoursewb | 12 hours | 0 | 0 | |
| 4.3 GB | JackieALF | 1 day | 0 | 0 |
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