Help the MuscleHub gym determine the best fitness test format by conducting A/B testing. 

A/B Test for MuscleHub

Nosh Mish Mosh is a food startup with a cool new idea. Help them make data driven decisions by analyzing their user base.

A/B Testing at Nosh Mish Mosh

Analyst the A/B test data from ShoeFly.com using aggregate measures.

A/B Testing for ShoeFly.com

Use data visualizations to understand trends and relationships in commercial flight data.

Airline Analysis

Use your knowledge of context managers in Python to help Aisha’s Greetings - a card printing company that prints greeting cards.

Aisha's Greetings

In this project, you will explore data on Algerian forests and run multiple linear regression models using variables including temperature, humidity, and fire risk.

Algerian Forest Fires

Use AI and SQL to analyze the rise of AI. 

Analyze AI Systems with SQL

Act as a 'Yahoo Finance' data analyst to generate a stock profile for Netflix.

Analyze and Visualize Netflix Stock Data

Analyze website domain data using DataFrames, SQL, and RDDs with the big data tool PySpark.


Analyze Common Crawl Data with PySpark

Create a data science project for your portfolio to demonstrate your technical skills in analyzing data with Python.


Analyze Data with Python Portfolio Project

Query Hacker News data using SQL to discover trends.

Analyze Hacker News Trends

Predict winning NFL games from game stats using logistic regression. Then find out which game stats are most important to your model.

Analyze NFL Stats with Python

Use sentiment analysis and natural language processing to discover how Taylor Swift's underlying themes and vibes have changed throughout her career.

Analyze Taylor Swift Lyrics with Python

Visualize traffic safety data and analyze the relationship between collisions and smartphone usage over time

Analyze Traffic Safety Data with Python

Query from two tables that contain Twitch’s stream viewing data and chat room usage data.

Analyze Twitch Gaming Data

Practice planning and implementing an A/B test.

Analyzing Farmburg's A/B Test

Analyze misleading data visualizations and use best practices to create effective visualizations.


Analyzing Misleading Visualizations: Green Lake Auto

Use PySpark SQL and DataFrames to analyze Wikipedia clickstream data

Analyzing Wikipedia Clickstreams with PySpark

In this project, you’ll take a basic data visualization to the next level using the principles of visual design theory. Apply balance, contrast, color, and other principles to create a polished visualization about electric vehicle charging infrastructure, global trade, or a topic and dataset of your own choice.

Applying Visual Design Principles to Data Visualization

In this project, we're going to practice functions and conditionals in Python so you can hone your skills and feel confident taking them to the real world.
Why? Ever wanted to automate your math homework? Time to build something in Python that does just that.

Area Calculator

Answer business questions about the performance of marketing campaigns for CoolTShirts.com, an innovative apparel shop.

Attribution Queries

Help Betty figure out how much she needs to buy using NumPy arrays describing her recipes.

Betty's Bakery

Analyze and interpret data from the National Parks Service on the status of endangered species in some of the parks. Use your Python and statistics skills to better understand the status of various species.

Biodiversity in National Parks

Display your initials on screen in block characters to create an ASCII art.

Block Letters

Use your pandas and matplotlib skills to analyze and visualize the FoodWheel dataset.

Board Slides for FoodWheel

In this project, we'll look at an online bookseller's database and think about how to improve it using indexes.

Book Store Indexes

This project is a step-by-step guide to create a restaurant menu database schema using PostgreSQL that closely models a real-life restaurant.

Build A Menu For Bytes Of China

This project is an overview of all material covered in the PostgreSQL constraints lesson and asks learners to apply different datatypes, nullability constraints, check constraints, unique constraints, and primary and foreign key constraints on new and existing tables.



Building an Inventory Database with PostgreSQL

Practice calculating churn rates using SQL.

Calculating Churn Rates

In this project, you will learn how to use the basics of Python syntax and data to make calculations. 

Calculating Population Change Over Time

In this project, you will learn how to use the basics of R syntax and operations to make calculations.



Calculating Population Change Over Time with R

Classify tumors as either malignant or benign using K-Nearest Neighbors.

Cancer Classifier

In this project, you will use your knowledge of mean, median and mode to make conclusions about three boroughs in New York City: Manhattan, New York City, and Queens.

Central Tendency for Housing Data

Use BeautifulSoup to scrape a site that contains over 1700 expert ratings of different chocolate bars. Then, put the data you find into Pandas and analyze the results!

Chocolate Scraping with Beautiful Soup

In this project, you will create a neural network that classifies mortality due to heart disease.

Classification

Build a deep learning model with TensorFlow to detect and classify infections from real X-ray scans.

Classify X-rays With Machine Learning

In this project, you will use a Convolutional Neural Network (CNN) to classify galaxies.

Classifying Galaxies

Fine-tune pre-trained BERT transformers from Hugging Face in PyTorch to classify IMDB movie reviews.

Classifying IMDB Movie Reviews with BERT Transformers

Train and evaluate a CNN to detect tumors in histopathological scans from the PatchCamelyon dataset.

Classifying Microscopic Histopathology Images with PyTorch

Use your knowledge of dplyr and tidyr to clean up this dataset containing a bunch of census data collected by the US government.

Cleaning US Census Data

Use your pandas and regex skills to clean up this dataset containing a bunch of census data collected by the US government.

Apply your knowledge of window functions to explore real climate data from each state in the United States.

Climate Change

Use your data visualization skills to explore the night sky and model the Orion Constellation.

Constellations

Compare linear regression models to predict housing prices on Craigslist.

Craigslist Analysis

Build fluency in SQL manipulation. We're going to practice creating tables in SQL so you can hone your skills and feel confident taking them to the real world.

Create a Table

Analyze hotel cancellations using AI and Python.

Create Analytics with AI: Hotel Cancellations

Use NumPy to solve statistical questions about a cereal dataset. 

CrunchieMunchies

51 Cent is a digital currency exchange headquartered in San Francisco, California. They broker exchanges of Bitcoin, Bitcoin Cash, Ethereum, and Litecoin with fiat currencies in around 32 countries. Help them analyze their January data using SQL aggregate functions!

Cryptocurrency Exchange

In Codestrips, you'll build a back-end to support a small comic strip creation app. Using Express.js and Node-SQLite, create a new database, build the proper table, and create GET and POST routes to provide access to and the ability to create new comic strips.

Cumulative Project: Codestrips

Bring together all of your data analytics skills into a portfolio project. Clean, analyze, and visualize, a dataset and then compile your results into a portfolio-worthy report.

Data Analytics Final Portfolio

Bring together all of your data skills skills into a portfolio project. Clean, analyze, and visualize, a dataset and then compile your results into a portfolio-worthy report.

Data Scientist Final Portfolio Project

In this project, you will curate your projects and code to create a job search-ready portfolio for your data scientist job search. You will need to create your own files, write your own code, and organize your work into your own site or repository. We’ll provide you with high-level tasks to guide your portfolio creation and ensure that it covers everything it should to showcase your skills.

We will also offer tips on how to make your portfolio stand out, but you are responsible for deciding what goes into your portfolio and what doesn’t. There are nearly infinite options for how to display your work, so treat this project as a starting point. In all likelihood, your portfolio will continue to grow throughout your career.

Have fun!


Data Scientist Interview Preparation Portfolio-Building Project

In this project, identify key insights and use the hook-insight-action framework to curate data visualizations and context into a meaningful data story. 

Data Storytelling: Green Lake Auto

Create a data science project for your portfolio to demonstrate your skills with data visualization!

Data Visualization Portfolio Project

In this project, learners will normalize a database table containing data from a furniture store by creating a new set of tables that contain all of the same information. Learners will then have a chance to explore how data modifications and queries differ before and after normalization. 

Database Normalization at Fred's Furniture

In this project we will be working with a small database of customer information and how to improve it with triggers.

Database Triggers

Use collections, datasets, and dynamic pages to display and collect information on a blog.

Datasets: National Parks Adventures

Do you remember Davie's Burgers from our Learn CSS course? Well, the business has been booming and it is now looking to place a funny and catchy advertisement in a local subway station. Help them dig into their `orders` data to see if there is anything interesting in there!

Davie's Burgers Subway Ad

It's the day of a citywide track race and you're helping out your friends!



Day of the Race

You will create a regression deep learning model that predicts an applicant's graduate admissions chances based on various parameters, such as grades, test scores, and program rating.

Deep Learning Regression with Admissions Data

Use histograms to explain exam score distributions in a math class.

Describe Exam Grade Distributions

Determine the number of defective products made at a factory on a given day. Apply concepts from the Poisson distribution, including random variables, the probability mass function, the cumulative distribution function, and expected values.

Detecting Product Defects with Probability

Use your knowledge of models and databases to programmatically help the owners of Djaunty Rent-a-Bike build out their rental system!

Djaunty Rent-a-Bike

In this next project, we're going to practice loops in Python so you can hone your skills and feel confident taking them to the real world.
Why? Being able to read and pull a file's data and then loop through each line will give you some serious power.

DNA Analysis

Given that a student answered a question correctly, what is the probability that she really knows the material?

Dr. Dirac's Statistics Midterm

Use your seaborn visualization skills to perform EDA on the Kiva dataset.

EDA with Kiva

Inspect, clean, and validate a dataset on diabetes prevalence among females of Pima Indian heritage.

EDA: Diagnosing Diabetes

See how survey responses compare to actual election results using binomial distributions. 

Election Results

In this project you will categorize emails using a Naive Bayes Classifier.

Email Similarity

In this project, you will practice further with creating generators to retrieve and iterate through streams of data as well as using various methods to manipulate the generator data.

Event Coordinator

Predicting employee attrition is challenging for HR departments, as it helps organizations retain valuable talent and reduce turnover costs. However, AI models used in such decisions must be transparent and interpretable, ensuring that HR professionals can trust and understand the predictions.

In this project, we will use the IBM HR Analytics Employee Attrition Dataset to predict whether an employee will likely leave the company. We will train different machine learning models and apply Explainable AI (XAI) techniques to interpret their predictions.

By the end of this project, we will have a fully interpretable pipeline that can help HR professionals make informed, fair, and data-driven decisions regarding employee retention.

Explainable AI in Employee Attrition Prediction

This project demonstrates how to use the LIME (Local Interpretable Model-agnostic Explanations) library to understand and explain predictions made by a machine learning model for breast cancer diagnosis. Using the Wisconsin Breast Cancer [dataset](https://archive.ics.uci.edu/dataset/17/breast+cancer+wisconsin+diagnostic), we analyze how individual features, such as mean radius, texture, and smoothness, influence the model's decision to classify a tumor as benign or malignant. By visualizing LIME values, we gain insights into the contribution of each feature to the model's predictions, enabling better transparency and trust in AI-driven healthcare diagnostics.

Explaining Breast Cancer Diagnosis Predictions with LIME

This project demonstrates how to use SHAP (SHapley Additive exPlanations) to interpret the predictions of a machine learning classification model for breast cancer diagnosis. Using the Wisconsin Breast Cancer [dataset](https://archive.ics.uci.edu/dataset/17/breast+cancer+wisconsin+diagnostic), we analyze how individual features, such as mean radius, texture, and smoothness, influence the model's decision to classify a tumor as benign or malignant. By visualizing SHAP values, we gain insights into the contribution of each feature to the model's predictions, enabling better transparency and trust in AI-driven healthcare diagnostics.

Explaining Breast Cancer Diagnosis Predictions with SHAP

Use your knowledge of DataFrames, reader, and dplyr to explore this dataset about cars from 1985. 

Explore the 1985 Cars Dataset

Use your bar chart analysis skills to the test with a fun mushroom dataset!

Exploring Mushrooms

Summarize the features of a dataset about student performance at two different schools.

Exploring Student Data

Begin to grasp the environmental impact of transformer models by experimenting with decoders and the CodeCarbon emissions tracking library.

Exploring Transformers and their Carbon Footprint

In this project we will be offering our services to a cool new startup named Familiar. We will be using statistical techniques to make statements and draw conclusions about Familiar's userbase.

Familiar: A Study In Data Analysis

In this project we will be offering our services to a cool new startup named Familiar. We will be using statistical techniques to make statements and draw conclusions about Familiar's user base.

Analyze dog adoption data for a pet startup.

FetchMaker

In this project we will practice different hypothesis tests by analyzing dog data from FetchMaker, the hottest new business. We will be looking for significant differences between dog breeds. Un-leash your newfound knowledge on these statistical challenges!

Use decision trees to predict what continent a flag comes from based on features like color and shape.

Find the Flag

Finetune a generative language model on the text of Mary Shelley's Frankenstein, using either QLoRA or performing a full finetune.

Finetuning a Generative Language Model

Use deep learning to predict forest cover type based on cartographic variables.

Forest Cover Classification

Investigate Frida Kahlo's work in the project using your own computer!

Frida Kahlo Retrospective

Investigate Frida Kahlo’s work using Python lists!

Frida Kahlo Retrospective Off-Platform Project

In this project you will learn about the differences between GPT-1 and GPT-2 models and practice your ability to build your own GPT model from scratch on a training dataset of your choice.

From GPT-1 to GPT-2

Create neural networks in PyTorch to generate text using Mary Shelley's novel Frankenstein.

Generating Text with Frankenstein Using PyTorch 

Let's prepare to teach physics by writing some Python functions.

Getting Ready for Physics Class

Use your knowledge of Python files to take down an evil hacker once and for all. 

Hacking The Fender

In this project, you will be using K-Means clustering and scikit-learn to cluster images of handwritten digits.

Handwriting Recognition using K-Means

Use boxplots to compare how hospitals in different states charge patients for medical procedures.

Healthcare in Different States

Investigate risk factors for heart disease using descriptive statistics and hypothesis tests.

Heart Disease Research Part I

Heart Disease Research Part II

Fit a line to data about the honeybee population decline in the United States.

Honey Production

Write functions to organize and manipulate data about Category 5 Hurricanes. By using dictionaries and lists, you can easily access the data you want and present it in different ways.

Hurricane Analysis

Use NumPy and linear algebra knowledge to do fun image transformations!

Image Transformations with NumPy

In this project, you will design, train, and evaluate a neural network model performing the task of regression to predict the life expectancy of countries using this dataset using Python and TensorFlow!

Implementing Neural Networks

Let's add some more complex indexes to our book store database!

Projects in data science

All projects in data science

A/B Test for MuscleHub

A/B Testing at Nosh Mish Mosh

A/B Testing at Nosh Mish Mosh

A/B Testing for ShoeFly.com

Airline Analysis

Aisha's Greetings

Algerian Forest Fires

Analyze AI Systems with SQL

Analyze and Visualize Netflix Stock Data

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