Data Analysis Fundamentals

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Mentor Based

Program Syllabus

Module 1

About This Course

The Advanced Data Analysis Fundamentals program is meticulously designed for academicians and researchers who wish to elevate their analytical capabilities. This course delves deep into statistical methods, predictive analytics, and big data technologies, empowering participants to lead data-centric projects and innovate in their respective fields.

Module 2

Aim

This program aims to equip PhD scholars and academicians with deep analytical skills and advanced techniques in data analysis. It focuses on the sophisticated methods needed to interpret complex datasets and translate them into actionable insights, fostering data-driven decision-making in academic and applied research settings.

Module 3

Program Objectives

Develop proficiency in handling and analyzing large and complex datasets.
Master the use of advanced statistical methods and predictive analytics.
Implement big data solutions for real-time and scalable data analysis.
Foster ethical practices in data management and analysis.
Enhance ability to communicate analytical findings effectively to influence decision-making.

Module 4

Program Structure

Foundational Statistics for Data Analysis
- Advanced statistical theories and applications
- Multivariate statistical methods
- Bayesian data analysis techniques
Predictive Analytics and Machine Learning
- Regression analysis and predictive modeling
- Machine learning algorithms for data prediction
- Evaluation metrics for model performance
Big Data Technologies
- Tools and techniques for managing big datasets
- Introduction to Hadoop and Spark ecosystems
- Real-time data analysis frameworks
Data Visualization and Interpretation
- Advanced visualization tools and techniques
- Interactive dashboards and data storytelling
- Visualizing high-dimensional data
Data Ethics and Governance
- Data privacy, security, and ethical use
- Regulatory compliance and data governance
- Bias, fairness, and accountability in data analysis
Capstone Project
- Application of advanced data analysis in a real-world research project
- Presentation and critical review of findings

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.