With our part-time Python fullstack development bootcamp students learn our core Python fullstack curriculum then have the option to dig deeper by applying it to specific industries by choosing an industry focus such as FinTech, Blockchain or Medicine.
We emphasize Python due to its speed and analytical capabilities. It is popular in areas including finance and data analysis, and is used by companies in multiple industries such as Bank of America, JP Morgan, BuzzFeed and Pinterest. It has been ranked as the highest paid coding language for recent bootcamp grads.* Python is known for its efficiency yet simplicity. Python has numerous open-source libraries and is actually named after the Monty Python movie!Other Languages
Curriculum is heavily project based with emphasis on teamwork. Past projects includes:
- Botserver – Allows businesses to interact with their community via artificial intelligence chatbots.
- Valorem – Commercial real estate data aggregator.
- Medical Map – Proof of Concept for real MedTech startup.
- PolitiPic – Predicts voter outcomes using facial recognition.
- MoneyMusic – Uses a recommendation engine to creates playlists for users based on their Spotify library.
Yodlee/Envestnet, Reuters, Bloomberg, IBM, Monax and more.
Upon graduation of this program, you will be able to develop applications for the finance industry. Samplepast projects include:
- Flexinvest – Crowdfunds Wall Street investments
- Market Tracker – Graphs stock prices related to tweets
- FinFormat – Personalized financial planning application
- Jade Lizard – Options strategy to maximize returns
Created with industry professionals and featured in Bloomberg, our blockchain course also builds off of our core Python Fullstack curriculum. Topics in the blockchain track include solidity, smart contracts, cryptocurrency, public vs private blockchains, ethereum, Bitcoin, enterprise blockchains and more. All projects are blockchain related and can pertain to any industry.Quant-Algo
In this curriculum created in partnership with a leading statistics – arb hedge fund, we’ll help you understand core statistical concepts and develop the tools for data analysis. Classes emphasize model creation and validation along with theoretical skills and statistical modeling interference.
We’ll help you learn now to utilize Python’s advanced data libraries including pandas, numpy, scikit-learn, and more. We’ll also delve into statistical topics such as summary statistics, regression, time series, hypothesis testing, and much more.
Other areas that we will cover include:
Python primer, stats concepts, time series – forecasting model, sample models, trading algorithms, model fit analysis, analyzing risk, factor models and quant applications.
Although this course is suitable for all industries, for those who choose a finance focus education on algorithms will be geared towards investments. We’ll prime you and connect you with our network for a career at a bank, hedge fund and/or other company that you seek out.Computers are needed. Some classes may suggest downloads be done beforehand. All students should bring any other material they may need to learn (pens, paper, etc)