📊 Udacity Data Analyst Nanodegree

Focus areas:

• Data Wrangling
• Data Analysis using python
• Data Analysis using PostgresSQL
• Machine Learning
• Data Visualization

Period: Nov 2024 - Jan 2025 (estimated completion)

##📚 Projects Click on the project title to view my projects! 🙂

Part 1: Data Analysis and Descriptive Statistics

🎞️ Investigate a Movie Dataset

Analyzing a TMDB Dataset with over 10,000 movies with 1D and 2D analysis

🧠 Skills/Libraries used

• Python
• Pandas
• Numpy
• Data Visualization
• Data Wrangling

❓Questions explored

• What is the distribution of movie budgets in this dataset?
• Which genres have the best and worst popularity on average? (2d analysis)

🛍️ Analyze A/B Test Results

Understanding the results of an A/B test run by an e-commerce website utilizing descriptive statistics

🧠 Skills/Libraries used

• Python
• Satsmodel
• Pandas
• Numpy

Part 2: Advanced Data Wrangling and Data Modeling

🎓 Does Prestige Pay?

Investigate correlation between college tuition and global ranking

🧠 Skills/Libraries used

• Python
• Pandas
• Numpy
• Data Visualization
• Data Wrangling

❓Question explored

• Is there a correlation between student tuition and school ranking?

🎧 Create Database for Music Streaming Company

Create database for company looking to analyze data they have collected

🧠 Skills/Libraries used

• PostgresSQL
• Database Creation

Part 3: Data Analysis with R

🚲 Explore Bikeshare Data

Explore bike share data from three different cities

🧠 Skills/Libraries used

• R
• Data Visualization

❓Question explored

• How do the number of subscribers and customers vary for each location
• What is the distribution of trip durations in a DC?
• What time of day is most common for users in Chicago?

Part 4: Supervised and Unsupervised Machine Learning

💵 Finding Donors

Employ several supervised algorithms to accurately model individuals' income

🧠 Skills/Libraries used

• SKlearn
• Data Visualization
• Machine Learning Algorithms

❓Question explored

• What is the most accurate model to predict if a person makes over $50,000

📬 Identify Customer Segments

Employ unsupervised algorithms to identify segments in the population

🧠 Skills/Libraries used

• SKlearn
• Data Visualization
• Machine Learning Algorithms