Data Manipulation with Pandas and NumPy

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Mentor Based

Program Syllabus

Module 1

About This Course

The Advanced Data Manipulation with Pandas and NumPy program is meticulously designed for those in data-intensive fields who seek to leverage the full potential of Python for high-level data analysis. This course focuses on providing hands-on expertise in efficiently handling, processing, and analyzing large datasets with Pandas and NumPy, crucial for cutting-edge research and analytics.

Module 2

Aim

This program aims to empower PhD scholars and academicians with the advanced skills necessary to master data manipulation using Pandas and NumPy, the backbone libraries for data analysis in Python. Participants will learn sophisticated techniques for data cleaning, transformation, and rapid numerical computing to drive analytical research and data-driven decisions in complex scientific domains.

Module 3

Program Objectives

Master the use of Pandas and NumPy for advanced data manipulation.
Conduct complex data analyses with efficiency and precision.
Develop robust data workflows suitable for large-scale datasets.
Implement and interpret sophisticated statistical analyses.
Translate complex datasets into actionable insights through visual storytelling.

Module 4

Program Structure

Advanced Foundations of Pandas and NumPy
- In-depth exploration of data structures in Pandas and NumPy.
- High-performance data manipulation and indexing techniques.
Complex Data Operations
- Merging, joining, and concatenating large datasets.
- Grouping and aggregating data for detailed analysis.
Time Series Analysis with Pandas
- Managing date and time data.
- Techniques for resampling, time shifts, and window functions.
Numerical Computing with NumPy
- Advanced array operations and broadcasting.
- Utilizing ufuncs for rapid processing and computations.
Optimizing Data Workflows
- Enhancing performance and scalability of data operations.
- Memory management and in-place operations for large data sets.
Visualization and Presentation of Data
- Integrating Pandas and NumPy with Matplotlib and Seaborn for insightful data visualizations.
- Best practices in visual data presentation.
Capstone Project
- Application of advanced data manipulation techniques in a real-world project.
- Synthesizing and presenting findings to an academic or professional audience.

Lead Instructor

Dr. Sarah Chen

PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.