Udemy - Python for Data Science Pro - The Complete Mastery Course

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Udemy - Python for Data Science Pro - The Complete Mastery Course (Size: 1 GB)
  1 - Variables data types and operators.mp4 30 MB
  10 - Sorting and Filtering Data.mp4 35.5 MB
  11 - Grouping and Aggregation.mp4 31.9 MB
  12 - Basic Plots Line Bar Scatter.mp4 39.1 MB
  13 - Customizing Plots.mp4 58.9 MB
  14 - Subplots and Figures.mp4 26.7 MB
  15 - Creating Interactive Charts.mp4 60.6 MB
  16 - Measures of Central Tendency.mp4 29.5 MB
  17 - Measures of Variability.mp4 25.6 MB
  18 - Normal Binomial and Other Distributions.mp4 47.8 MB
  19 - Null and Alternative Hypotheses.mp4 33.5 MB
  2 - Control Flow Conditionals and Loops.mp4 17.2 MB
  20 - Feature Scaling and Normalization.mp4 37.9 MB
  21 - Encoding Categorical Variables.mp4 56.9 MB
  22 - Handling Imbalanced Data.mp4 49.5 MB
  23 - Linear and Logistic Regression.mp4 100.9 MB
  24 - Introduction to Time Series Data.mp4 24.1 MB
  25 - Decomposition ARIMA Models.mp4 71.1 MB
  26 - Text Preprocessing.mp4 28.8 MB
  27 - Sentiment Analysis.mp4 20.2 MB
  3 - Functions and Modules.mp4 20.1 MB
  4 - Understanding Arrays and Matrices.mp4 48.9 MB
  5 - Array Operations.mp4 33.7 MB
  6 - DataFrames and Series.mp4 19.9 MB
  7 - Data Cleaning and Preparation.mp4 33.1 MB
  8 - Handling Missing Data.mp4 25.8 MB
  9 - Merging and Joining Data.mp4 30.5 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 29 total files

Description


Python for Data Science Pro: The Complete Mastery Course

https://DevCourseWeb.com

Published 8/2024
Duration: 3h59m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 1.01 GB
Genre: eLearning | Language: English

Become a Data Science Pro: Master Data Analysis, Visualization, and Machine Learning with Python

What you'll learn
What is Python Data Science and Workflow?
Control Flow: Conditionals and Loops
Understanding Arrays and Matrices
Data Cleaning and Preparation
Merging and Joining Data
Subplots and Figures
Measures of Central Tendency
Measures of Variability
Normal, Binomial, and Other Distributions
Types of Machine Learning: Supervised, Unsupervised, Reinforcement Learning
Handling Imbalanced Data
Linear and Logistic Regression
Sentiment Analysis

Requirements
No prior knowledge is required!

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