Engineering Data Analysis – Introduction

Course Title: Engineering Data Analysis

Course Duration: 54 Hours (9 Hours/Week for 6 Weeks)

Course Description:

This course aims to introduce students to the principles and techniques of data analysis in engineering. The course focuses on the application of statistical methods, predictive modeling, data mining, and data visualization in solving real-world engineering problems. Students will gain proficiency in using advanced computational tools and software for managing, analyzing, and interpreting large sets of data.

Week 1: Introduction to Data Analysis and Statistics in Engineering

1. Introduction to the Course – 1.5 hours
2. Basics of Statistics in Engineering – 1.5 hours
3. Descriptive Statistics and Data Visualization – 2 hours
4. Probability Theory and Random Variables – 2 hours
5. Workshop: Hands-On Statistics – 2 hours

Week 2: Data Collection and Preprocessing

1. Types of Data in Engineering – 1.5 hours
2. Data Collection Methods and Ethics – 2 hours
3. Preprocessing: Cleaning, Transforming, and Reduction – 2 hours
4. Workshop: Data Collection and Preprocessing Exercise – 3.5 hours

Week 3: Exploratory Data Analysis

1. Introduction to Exploratory Data Analysis – 1.5 hours
2. Hypothesis Testing and Confidence Intervals – 2 hours
3. Correlation and Regression Analysis – 2 hours
4. Workshop: Exploratory Data Analysis – 3.5 hours

Week 4: Advanced Statistical Methods

1. Multivariate Statistical Methods – 2 hours
2. Time Series Analysis and Forecasting – 2 hours
3. Introduction to Bayesian Analysis – 2 hours
4. Workshop: Advanced Statistical Methods – 3 hours

Week 5: Predictive Modeling and Machine Learning

1. Introduction to Predictive Modeling – 1.5 hours
2. Supervised Learning Techniques – 2 hours
3. Unsupervised Learning Techniques – 2 hours
4. Workshop: Predictive Modeling and Machine Learning – 3.5 hours

Week 6: Data Visualization and Reporting

1. Effective Data Visualization Techniques – 1.5 hours
2. Data Storytelling – 2 hours
3. Reporting and Communicating Data Analysis – 1.5 hours
4. Workshop: End-to-End Data Analysis Project – 4 hours

Course Assessment:

1. Weekly Workshops & Assignments – 40%
2. Mid-Course Test (End of Week 3) – 20%
3. End-of-Course Project and Presentation – 40%