Introduction to Matplotlib

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Introduction to NumPy and Matplotlib for Scientific Computing

Introduces NumPy and Matplotlib, essential tools for scientific computing and data visualization in Python.

NumPy Arrays and Graphical Representations: Introduction

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Introduction to Jupyter Notebook

Introduces setting up the environment, Git basics, and Jupyter Notebook features with practical examples.

Car Data Analysis: ICC Workspace

Explores car data analysis in Python using the ICC workspace and covers reading, processing, and analyzing car information.

Data Science with Python

Covers Python basics, Pandas, data manipulation, visualization, and machine learning.

Numerical Methods: Stopping Criteria, SciPy, and Matplotlib

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Data Visualization: Techniques, Tools & Concepts

Covers data visualization techniques, tools, and concepts for effective data representation.

Air Pollution Data Analysis

Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.