Workshops, study groups, resources and 1-on-1 assistance with putting together your application materials, submitting your resume, prepping for interviews, connecting with alumni/employers, and navigating your job offers.

Workshops, study groups, resources and 1-on-1 assistance with putting together your application materials, submitting your resume, prepping for interviews, connecting with alumni/employers, and navigating your job offers.

The Erdős Institute's signature Data Science Boot Camp has been running since May 2018 thanks to the generous support of our sponsors, members, and partners. Due to its popularity, we now offer our boot camp online three times per year in two different formats: a 1-month long intensive boot camp each May and a semester long version each Spring & Fall.

The Erdős Institute's signature Data Science Boot Camp has been running since May 2018 thanks to the generous support of our sponsors, members, and partners. Due to its popularity, we now offer our boot camp online three times per year in two different formats: a 1-month long intensive boot camp each May and a semester long version each Spring & Fall.

Welcome to the UX Research course! The lessons concentrate on research-related industry roles particularly popular among those in the social sciences, arts, and humanities: UX research and related fields, like market research and consumer insights.

There are three projects for this course. In order to receive a UX Research certificate, you must submit all 3 projects, as well as a final project summary. Details of these projects are below.

In this reading course, we will cover introductory sections from industry-standard texts. The material will cover basic quantum algorithms (Grover, Quantum Counting, Quantum Phase Estimation, Shor, etc), selected advanced algorithms (for example, QAOA and other Binary Optimization techniques etc), and the fundamentals of Quantum Error Correction. I will also try to incorporate as much hands-on coding problems, with Qiskit, as possible.

There will be weekly meetings (tentatively 2, 45-minute meetings a week). I will also hold weekly office hours on zoom.

The Introduction to Quantitative Methods in Finance course is designed to provide participants with a solid grasp of fundamental probabilistic techniques applied in financial markets. With a specific focus on Black-Scholes modeling of European options, the course capitalizes on the availability of closed-form solutions for European option expected values. This facet not only facilitates the evaluation of model predictions but also underscores the practical relevance of the concepts covered.

Workshops, study groups, resources and 1-on-1 assistance with putting together your application materials, submitting your resume, prepping for interviews, connecting with alumni/employers, and navigating your job offers.

Workshops, study groups, resources and 1-on-1 assistance with putting together your application materials, submitting your resume, prepping for interviews, connecting with alumni/employers, and navigating your job offers.

During the first half of the cohort, there are six Job Help lectures that are common to all Launch bootcamps. The recordings / slides will be found on this page. During the second half of the cohort, each Launch bootcamp will be focused on technical interview preparation. The details about study materials and schedules will be on the course page for each Launch bootcamp.

Workshops, study groups, resources and 1-on-1 assistance with putting together your application materials, submitting your resume, prepping for interviews, connecting with alumni/employers, and navigating your job offers.

In this bootcamp, we will develop the skills needed to complete a data science project from start to finish. This includes defining a problem in quantitative terms, identifying key performance indicators (KPIs), acquiring and cleaning data, exploring patterns and trends, and transforming raw data into meaningful variables. We will then build models for prediction and inference, focusing primarily on supervised learning methods for regression and classification.

Welcome to the UX Research Boot Camp! The lessons concentrate on research-related industry roles particularly popular among those in the social sciences, arts, and humanities: UX research and related fields, like market research and consumer insights.

There are three projects for this course. In order to receive a UX Research certificate, you must submit all 3 projects, as well as a final project summary. Details of these projects are below.

Our materials touch on the following content to varying degrees:
• Plotting in Python: matplotlib, seaborn, plotly, and bokeh
• Web browser visualizations: HTML, CSS, SVG, and d3.js
• Basic Tableau
• Basic design principles

Note: our asynchronous mini-courses do not have a project component and do not offer certification. Any references to either projects or certificates you find in these course materials are remnants of earlier iterations of the course where these components were present.

The Erdős Institute's signature Data Science Boot Camp has been running since May 2018 thanks to the generous support of our sponsors, members, and partners. Due to its popularity, we now offer our boot camp online three times per year in two different formats: a 1-month long intensive boot camp each May and a semester long version each Spring & Fall.

The Erdős Institute's signature Data Science Boot Camp has been running since May 2018 thanks to the generous support of our sponsors, members, and partners.

Our goal is to provide you with the skills and mentorship necessary to produce a portfolio worthy data science project.

We will learn the fundamentals of data science including: data collection, data cleaning, exploratory data analysis, inferential statistics, supervised and unsupervised machine learning techniques, and the basics of neural networks.

Each week of the course we will have a live lecture, a problem session, and an optional "math hour" and office hour.

In order to receive a Data Science certificate you must complete a portfolio worthy project in collaboration with a team of your peers.

This boot camp is designed to provide participants with a solid grasp of fundamental probabilistic techniques applied in financial markets.

Welcome to the UX Research Boot Camp! The lessons concentrate on research-related industry roles particularly popular among those in the social sciences, arts, and humanities: UX research and related fields, like market research and consumer insights.

There are three projects for this course. In order to receive a UX Research certificate, you must submit all 3 projects, as well as a final project summary. Details of these projects are below.

Welcome to the UX Research Boot Camp! The lessons concentrate on research-related industry roles particularly popular among those in the social sciences, arts, and humanities: UX research and related fields, like market research and consumer insights.

There are three projects for this course. In order to receive a UX Research certificate, you must submit all 3 projects, as well as a final project summary. Details of these projects are below.

In this boot camp, we will cover introductory sections from industry-standard texts. The material will cover basic quantum algorithms (Grover, Quantum Phase Estimation, Shor) and selected advanced topics (for example, Quantum State Preparation, Hamiltonian Simulation, Stabilizer/CCS codes).

There will be three ``mini-projects'' implementing both fundamental algorithms (for example, Grover's Search or Shor's algorithm) and current methods (for example, state-of-the-art quantum state preparation or error correction methods). You will have the option to select from a list of project ideas.

These will be announced every two weeks, starting on the second week, and you will have two weeks to submit your work.

The successful submission of these mini-projects is a requirement for the certificates of completion of the boot camp.

The Software Engineering for Data Scientists course is meant to help data scientists write production ready code as well as gain familiarity with the tools used to make models available to their users. The core idea we will be exploring is making code robust and re-usable across a team. This course can also serve as an introduction toward ideas used in ML Ops and Data Engineering.