Python for Data Science IBM Full Course | Analyzing Data with Python | Python Data Analysis

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Python for Data Science – IBM Full Course is a free, beginner‑friendly program that teaches how to use Python for data analysis and machine learning. The curriculum covers Python basics, essential data science packages, NumPy and Pandas for data manipulation, data preprocessing, exploratory data analysis, descriptive statistics, regression techniques, and an introduction to scikit‑learn. Hands‑on projects and coding demos reinforce the concepts. The course is organized into sections with timecodes: 00:00:00 Course Introduction, 00:01:44 Understanding the Data, 00:04:19 Python Packages for Data Science, 00:06:55 Importing and Exporting Data in Python, 00:11:14 Getting Started Analyzing Data in Python, 00:15:42 Accessing Databases with Python, 00:19:50 Data Pre‑processing in Python, 00:22:09 Dealing with Missing Values in Python, 00:28:15 Data Formatting, 00:31:48 Data Normalization, 00:35:32 Binning, 00:37:30 Turn Categorical Variable into Quantitative Variable in Python, 00:39:41 Exploratory Data Analysis, 00:41:10 Descriptive Statistics, 00:45:58 Group By in Python, 00:49:27 Correlation, 00:52:06 Correlation – Statistics, 00:54:52 Model Development, 00:56:45 Linear Regression and Multiple Linear Regression, 01:03:27 Model Evaluation Using Visualization, 01:08:20 Polynomial Regression and Pipelines, 01:12:55 Measures for In‑Sample Evaluation, 01:17:50 Prediction and Decision Making, 01:23:02 Model Evaluation, 01:30:41 Overfitting, Underfitting and Model Selection, 01:35:10 Ridge Regression, 01:39:47 Grid Search.