city_school_district_analysis

Analyzing the district wide standardized test results data by aggregate it to showcase obvious trends in school performance.

credit-risk-classification

Use various techniques to train and evaluate a model based on loan risk. I’ll use a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.

crowdfunding_etl

Build an ETL pipeline using Python and Pandas to extract and transform the data then create CSV files and use them to create an ERD and a table schema in order to use Postgres to create tables and explore the data.

cryptoclustering

Using Python and unsupervised learning to predict if cryptocurrencies are affected by 24-hour or 7-day price changes.

dalyalami

🎓 Welcome to my Github profile! I'm a recent graduate from the University of Toronto, equipped with a Certificate in Data Analytics and eager to kick-start my career in the field.

dalyalami.github.io

evaluating_food_hygiene_rating

Evaluating some of the food hygiene ratings data in order to help the UK Food Standards Agency journalists and food critics decide where to focus future articles.

exploring_suicide_rates_and_factors

This research project seeks to comprehensively investigate suicide rates and their underlying factors over the period from 1985 to 2020.

exploring_the_spectrum_of_suicide_rates

Explore the various factors that influence suicide rates, such as the impact of suicide prevention and support organizations, geographical variations, the interplay of age groups and generational factors, and make insightful comparisons with other leading causes of death.

home_sales

Determine key metrics about home sales data using SparkSQL and then use Spark to create temporary views, partition the data, cache and uncache a temporary table, and verify that the table has been uncached.

mars_news_scraping

Web-scrape and data analyse using both automated browsing with Splinter and HTML parsing with Beautiful Soup.

module-1-challenge

Excel

module_5_challenge_data_visualization

movie_recomendation

We are focused on developing a movie recommendation model that incorporates user ratings to provide personalized recommendations.

nonprofit_foundation_alphabet_soup

Using machine learning and neural networks, use the features in the provided dataset to create a binary classifier that can predict whether applicants will be successful if funded by Alphabet Soup.

python-api-challenge

python_challenge_module_3

sql-challenge

sqlalchemy-challenge

vba_challenge_module_2

Multiple_Year_Stock_Data