Data Manipulation with Pandas and NumPy Course – 4 weeks

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.

Aim

This program aims to empower PhD scholars and academicians with 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.

Program Objectives

Master Data Manipulation: Gain advanced proficiency in using Pandas and NumPy for handling large-scale datasets.
Conduct Complex Data Analyses: Implement efficient, accurate data operations for deep analytical insights.
Optimize Data Workflows: Develop robust workflows to handle and process large datasets with performance optimization.
Statistical Analysis: Conduct sophisticated statistical analysis and data operations with ease.
Data Visualization: Present complex data through compelling visual storytelling.

Program Structure

Module 1: Advanced Foundations of Pandas and NumPy

In-depth exploration of Pandas and NumPy data structures
Advanced indexing, selection, and manipulation techniques

Module 2: Complex Data Operations

Merging, joining, and concatenating large datasets
Grouping and aggregating data for detailed statistical analysis

Module 3: Time Series Analysis with Pandas

Techniques for managing time-based data
Resampling, time shifts, and rolling window functions

Module 4: Numerical Computing with NumPy

Advanced array operations and broadcasting
Using ufuncs for efficient processing and computation

Module 5: Optimizing Data Workflows

Improving performance for large-scale data processing
Memory management and in-place operations

Module 6: Visualization and Presentation of Data

Integration of Pandas and NumPy with Matplotlib and Seaborn
Best practices in visual storytelling and presentation

Module 7: Capstone Project

Application of advanced data manipulation in a real-world context
Presenting findings to academic or professional audiences

Participant’s Eligibility

Data Scientists, Researchers, and Academicians: Specializing in fields such as computer science, economics, statistics, or any discipline that involves advanced data analysis and manipulation.

Program Outcomes

Expertise in Data Handling: Mastery of complex data manipulation using Pandas and NumPy.
High-Level Data Analysis: Proficiency in performing advanced operations and computations on large datasets.
Optimization Skills: Ability to optimize workflows for better performance and efficiency.
Effective Data Presentation: Skills in presenting data visually, tailored to diverse audiences.
Research-Ready Skills: Preparedness for data-driven research and tackling analytical challenges across various fields.

Fee Structure

Standard Fee: INR 5,998 | USD 90
Discounted Fee: INR 2,999 | USD 45

Program Deliverables

Access to e-LMS
Real-Time Project for Dissertation
Project Guidance
Paper Publication Opportunity
Self-Assessment
Final Examination
e-Certification
e-Marksheet

Future Career Prospects

Lead Data Scientist: Leading teams to tackle complex data problems.
Data Engineering Specialist: Optimizing data architectures for large-scale systems.
Quantitative Research Analyst: Conducting data-driven research in finance and economics.
Bioinformatics Scientist: Analyzing biological data for breakthroughs in biotechnology.
Financial Modeler: Building advanced models for financial forecasting and risk analysis.
Academic Researcher in Data Science: Driving research and innovation in academic settings.

Job Opportunities

Research and Academic Institutions
Financial Institutions and Banks
Biotech and Pharmaceutical Companies
Tech and Software Development Firms
Government and Policy Research Organizations
Data Analytics and Consulting Firms

MODE	Online/ e-LMS
TYPE	Self Paced
LEVEL	Moderate
DURATION	4 weeks

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Data Manipulation with Pandas and NumPy Course – 4 weeks

Aim

Program Objectives

Program Structure