Udemy - Python for Data Science - The Complete Data Science Bootcamp

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3 GB
  • Uploaded Byfreecoursewb
  • Downloads15
  • Last checkedFeb. 12th '26
  • Date uploadedFeb. 12th '26
  • Seeders 1
  • Leechers9

Infohash : 2ECB44B7ACBB3FBD03C31867FF8CB5C514AB5611

Python for Data Science: The Complete Data Science Bootcamp

https://WebToolTip.com

Published 1/2026
Created by Muhammad Riaz Uddin
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 44 Lectures ( 3h 54m ) | Size: 3 GB

Python for Data Science: Perform Data Analysis, Visualization, and Machine Learning With Python

What you'll learn
✓ What is Data Science?
✓ Why Python for Data Science?
✓ Introduction to Jupyter Notebooks
✓ Variables, Data Types, and Operators
✓ Control Flow: Conditionals and Loops
✓ Working with Modules and Packages
✓ Error Handling and Assertions
✓ Introduction to Pandas: Series and DataFrames
✓ Reading & Writing Data (CSV, Excel, JSON)
✓ Data Cleaning & Preprocessing
✓ Handling Missing Values & Duplicates
✓ Data Transformation & Feature Engineering
✓ Creating, Indexing, and Slicing Arrays
✓ Mathematical Operations with NumPy
✓ Useful NumPy Functions for Data Science
✓ Introduction to Data Visualization
✓ Plotting with Matplotlib
✓ Seaborn for Statistical Graphics
✓ Advanced Charts: Heatmaps, Pairplots, and Violin Plots
✓ Identifying Patterns, Outliers & Trends
✓ Using Pandas Profiling & Sweetviz

Requirements
● No prior data science experience needed

Files:

[ WebToolTip.com ] Udemy - Python for Data Science - The Complete Data Science Bootcamp
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction to Data Science and Python
    • 1. What is Data Science.mp4 (31.2 MB)
    • 2. Why Python for Data Science.mp4 (37.9 MB)
    • 3. Introduction to Jupyter Notebooks.mp4 (11.9 MB)
    • 4. First Python Script “Hello Data ”.mp4 (58.1 MB)
    2 - Python Fundamentals for Data Science
    • 5. Variables Data Types and Operators.mp4 (64.4 MB)
    • 6. Control Flow Conditionals and Loops.mp4 (74.2 MB)
    • 7. Functions and Scope.mp4 (62.7 MB)
    • 8. Working with Modules and Packages.mp4 (81.1 MB)
    • 9. Error Handling and Assertions.mp4 (108.7 MB)
    3 - Working with Data Using Pandas
    • 10. Introduction to Pandas Series and DataFrames.mp4 (81.3 MB)
    • 11. Reading & Writing Data (CSV Excel JSON).mp4 (79.7 MB)
    • 12. Data Cleaning & Preprocessing.mp4 (117.0 MB)
    • 13. Handling Missing Values & Duplicates.mp4 (110.7 MB)
    • 14. Data Transformation & Feature Engineering.mp4 (109.2 MB)
    • 15. Grouping Sorting and Aggregating Data.mp4 (80.3 MB)
    4 - Numerical Computing with NumPy
    • 16. Arrays vs Lists.mp4 (64.6 MB)
    • 17. Creating Indexing and Slicing Arrays.mp4 (50.3 MB)
    • 18. Mathematical Operations with NumPy.mp4 (86.9 MB)
    • 19. Broadcasting and Vectorization.mp4 (49.5 MB)
    • 20. Useful NumPy Functions for Data Science.mp4 (96.5 MB)
    5 - Data Visualization
    • 21. Introduction to Data Visualization.mp4 (59.8 MB)
    • 22. Plotting with Matplotlib.mp4 (102.1 MB)
    • 23. Customizing Charts (Colors Labels Legends).mp4 (87.8 MB)
    • 24. Advanced Charts Heatmaps Pairplots and Violin Plots.mp4 (91.4 MB)
    • 25. Interactive Visualizations (optional Plotly Altair).mp4 (57.7 MB)
    6 - Exploratory Data Analysis (EDA)
    • 26. What is EDA.mp4 (53.0 MB)
    • 27. Identifying Patterns Outliers & Trends.mp4 (53.8 MB)
    • 28. Descriptive Statistics.mp4 (72.1 MB)
    • 29. Correlation Analysis.mp4 (47.1 MB)
    • 30. Using Pandas Profiling & Sweetviz (Optional).mp4 (63.9 MB)
    7 - Introduction to Statistics for Data Science
    • 31. Mean Median Mode Variance Standard Deviation.mp4 (55.3 MB)
    • 32. Probability Concepts.mp4 (43.9 MB)
    • 33. Hypothesis Testing.mp4 (41.4 MB)
    • 34. Confidence Intervals.mp4 (48.5 MB)
    • 35. Linear Regression Intuition.mp4 (90.4 MB)
    8 - Machine Learning with Scikit Learn
    • 36. What is Machine Learning.mp4 (38.7 MB)
    • 37. Supervised vs Unsupervised Learning.mp4 (72.9 MB)
    • 38. ML Workflow (Prepare Train Evaluate Tune).mp4 (77.2 MB)
    • 39. Regression Algorithms Linear Ridge Lasso.mp4 (108.8 MB)
    • 40. Classification Algorithms Logistic Regression KNN Decision Trees.mp4 (105.6 MB)
    • 41. Clustering K Means.mp4 (40.2 MB)
    9 - Advanced Topics (Optional Bonus)
    • 42. Introduction to Time Series Analysis.mp4 (85.6 MB)
    • 43. Intro to Deep Learning with TensorFlow Keras.mp4 (73.2 MB)
    • 44. Working with Big Data (Intro to PySpark).mp4 (83.3 MB)
    • Bonus Resources.txt (0.1 KB)

Code:

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