| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Introduction to Data Science and Python | |||
| 1. What is Data Science.mp4 | 31.2 MB | ||
| 2 - Python Fundamentals for Data Science | |||
| 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 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 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 | ||
| 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 | ||
| 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 |
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
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