Data Science : Begineer to Advance

Chapters

1Data Science Foundations and Workflow

2Python Programming Essentials for Data Science

3Working with Data Sources and SQL

4Data Wrangling with NumPy and Pandas

NumPy Arrays and Vectorization Broadcasting and Advanced Indexing Pandas Series and DataFrame Data Selection and Filtering Merging and Joining DataFrames Reshaping Pivot and Melt GroupBy and Aggregations Time Series in Pandas Text Data in Pandas Categorical and Sparse Data Missing Values Handling Apply Map and Vectorized UDFs Performance Tips and Memory Custom Functions and Pipelines Pandas IO and Chunking

5Data Cleaning and Preprocessing

6Exploratory Data Analysis and Visualization

7Probability and Statistics for Data Science

8Machine Learning Foundations

9Supervised Learning Algorithms

10Unsupervised Learning and Dimensionality Reduction

11Model Evaluation, Validation, and Tuning

12Feature Engineering and ML Pipelines

13Time Series Analysis and Forecasting

14Natural Language Processing

15Deep Learning, Deployment, and MLOps

Courses/Data Science : Begineer to Advance/Data Wrangling with NumPy and Pandas

Data Wrangling with NumPy and Pandas

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Transform raw data into analysis-ready datasets using vectorized operations and powerful tabular transformations with NumPy and Pandas.

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Reshaping Pivot and Melt

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