Resource Library
Access all course materials, readings, assignments, and supplementary resources in one centralized location.
Introduction to Data Analysis
An overview of the data analysis process, including methodologies, tools, and best practices for extracting insights from data.
Exploratory Data Analysis Project
Apply exploratory data analysis techniques to a real-world dataset and create visualizations to communicate findings effectively.
Data Cleaning Examples in Python
Jupyter notebook with examples of common data cleaning operations using Pandas, including handling missing data, removing duplicates, and standardizing formats.
Statistical Inference and Hypothesis Testing
An in-depth exploration of statistical inference methods and hypothesis testing frameworks for data-driven decision making.
Bayesian Methods in Modern Statistics
A collection of research papers exploring the latest applications of Bayesian statistics in data science, with practical case studies.
Mixed Effects Models in R
Implementation examples of linear and generalized linear mixed models using the lme4, nlme, and brms packages in R.
Neural Networks Architecture and Backpropagation
A deep dive into neural network architectures, activation functions, and the mathematics behind backpropagation for training.
Building a Neural Network from Scratch
Implement a feedforward neural network for classification without using deep learning libraries like TensorFlow or PyTorch.
PyTorch Implementation of CNN for Image Classification
Complete implementation of a convolutional neural network for image classification using PyTorch, including data loading, training, and evaluation.
Big Data Analytics Fundamentals
Introduction to big data concepts, Hadoop ecosystem, and distributed computing frameworks for large-scale data processing.
Hadoop MapReduce Implementation
Implement MapReduce algorithms for processing large datasets using Hadoop framework and Java programming.
Spark Streaming Applications
Real-time data processing examples using Apache Spark Streaming for continuous data analysis and monitoring.
Software Engineering Principles
Core software engineering concepts including design patterns, SOLID principles, and software development methodologies.
Design Pattern Implementation
Implement common design patterns including Singleton, Factory, Observer, and Strategy patterns in Java.
Git Version Control Workshop
Comprehensive Git tutorial covering branching, merging, conflict resolution, and collaborative development workflows.
Human-Computer Interaction Design
Principles of user interface design, usability testing, and user experience optimization for interactive systems.
Usability Testing Report
Conduct usability testing on a web application and create a comprehensive report with recommendations for improvement.
Prototyping with Figma
Interactive prototyping tutorial using Figma for creating user interface mockups and interactive prototypes.
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