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Syllabus and Projects for my Udacity Data Analyst Nanodegree

PART 0: Welcome to the Nanodegree

Analyze Bay Area Bike Share Data (optional)

Get started on your Nanodegree and learn how to make the most of Udacity's resources!

You’ll also do your first project analyzing bike rental data. It’s a great project to tackle during the first week in your Nanodegree to see if the program is a good fit for you!

PART 1: Statistics

Test a Perceptual Phenomenon

Use descriptive statistics and a statistical test to analyze the Stroop effect, a classic result of experimental psychology. Give your readers a good intuition for the data and use statistical inference to draw a conclusion based on the results.

Link to report

PART 2: Intro to Data Analysis

Investigate a Dataset (Using Python)

Choose one of Udacity's curated datasets and investigate it using NumPy and Pandas. Go through the entire data analysis process, starting by posing a question and finishing by sharing your findings.

Link to report

PART 3: Data Wrangling

Wrangle OpenStreetMap Data (Using Python, SQL)

Choose any area of the world in https://www.openstreetmap.org and use data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, to clean the OpenStreetMap data for a part of the world that you care about. Choose to learn SQL or MongoDB and apply your chosen schema to the project.

Link to report

PART 4: Exploratory Data Analysis

Explore and Summarize Data (Using R)

Use R and apply exploratory data analysis techniques to explore a selected data set for distributions, outliers, and anomalies.

Link to report

PART 5: Intro to Machine Learning

Identify Fraud from Enron Email (Using Python)

Play detective and put your machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.

Link to report

PART 6: Data Visualization (Learning)

Make Effective Data Visualization (Using D3.js)

Create a data visualization from a data set that tells a story or highlights trends or patterns in the data. Use either dimple.js or d3.js to create the visualization. Your work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.

Link to report

PART 7: A/B Testing (not learned)

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