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algorithmic-trading-bot

Combined my new algorithmic trading skills with existing skills in financial Python programming and machine learning to create an algorithmic trading bot that learns and adapts to new data and evolving markets.

arbitrage-opportunities-in-bitcoin

Using Python to sort through historical trade data for Bitcoin on two exchanges: Bitstamp and Coinbase. Your task is to apply the three phases of financial analysis to determine if any arbitrage opportunities exist for Bitcoin.

blockchain-wallets

Integrating the Ethereum blockchain network into an application in order to enable your customers to instantly pay the fintech professionals whom they hire with cryptocurrency.

blockchain-with-python

Built a blockchain-based ledger system, complete with a user-friendly web interface. This ledger should allow partner banks to conduct financial transactions (that is, to transfer money between senders and receivers) and to verify the integrity of the data in the ledger.

buildspace-solutions

crypto-algorithmic-trading-bot

We will be creating an algorithmic crypto trading bot that will use the Kraken API to get crypto prices. We will use machine learning to determine the trend of the market from historical data and determine the best strategies/indicators to use.

financial-databases-with-sql

Built a financial database and web application by using SQL, Python, and the Voilà library to analyze the performance of a hypothetical fintech ETF.

financial-simulations-and-apis

Built a tool to help credit union members evaluate their financial health. First, they should be able to assess their monthly budgets. Second, they should be able to forecast a reasonably effective retirement plan based on their current holdings of cryptocurrencies, stocks, and bonds.

gpt3-writer-starter

loan-qualifier

Applying software-engineering best practices to add new features and enhancements to the loan qualifier application

logistic-regression-and-imbalanced-learning

Used 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. Using my knowledge of the imbalanced-learn library, I used a logistic regression model to compare two versions of the dataset.

microsoft-data-science-for-beginners

10 Weeks, 20 Lessons, Data Science for All!

neural-networks

The business team has given a CSV file containing more than 34,000 organizations that have received funding from Alphabet Soup over the years. The CSV file contains a variety of information about each business, including whether or not it ultimately became successful.

nft-collection

This NFT collection brings together two massive industries allowing a gateway to the crypto world for basketball fans. The smart contract will randomly select and combine NBA player's last names, so that fans can build a collection of their favorite player's names. The holders can trade or sell their NBANFT on Opensea.

portfolio

quantitative-analysis-of-the-ark-etfs

Our goal is to see how much investment potential these ETFs have based on key risk-management metrics: the daily returns, standard deviations, Sharpe ratios, and betas. We will be working on a Jupyter Notebook and visualizing all of our data using hvplot to create interactive visualizations as well as running an MC Simulation at the end.

quantitive-analysis-with-python

Produced a Jupyter notebook that contains my data preparation, analysis, and visualizations for key risk and return metrics.

real-estate-rental-analysis

Used data visualization skills, including aggregation, interactive visualizations, and geospatial analysis, to find properties in the San Francisco market that are viable investment opportunities.

robo-advisors

I’m acting as a digital transformation consultant for a retirement plan provider. They want to increase their client portfolio—especially by engaging young people. Because machine learning and NLP are disrupting finance to improve the customer experience, I decide to create a robo advisor.

smart-contracts-with-solidity

Created a Solidity smart contract that accepts two user addresses. Your smart contract will use ether management functions to implement a financial institution’s requirements for providing the features of the joint savings account. These features will consist of the ability to deposit and withdraw funds from the account.

time-series-analysis

Analyzing a company's financial and user data in clever ways to make the company grow. As to find out if we have the ability to predict search traffic which can translate into the ability to successfully trade a stock.

tokenomics

KaseiCoin will be a fungible token that is ERC-20 compliant. You will launch a crowdsale that will allow people who are moving to Mars to convert their earthling money to KaseiCoin. The crowdsale contract that you create will manage the entire crowdsale process, allowing users to send ether to the contract and in return receive KAI, or KaseiCoin tokens.

unsupervised-learning

Combined financial Python programming skills with the new unsupervised learning skills that I acquired. You’ll create a Jupyter notebook that clusters cryptocurrencies by their performance in different time periods. Plotted the results so I can visually show the performance to the board.

valuing-microlending-loans

Python program that automates the tasks associated with valuing micro-lending loans.