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.

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