Walk into an interview with...

You can accelerate your AI career by building end-to-end projects that you are passionate about. Guided by mentors who are Kaggle champions, NASA scientists, researchers and principal data scientists.

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Why do students
love AI DEEP DIVE?

It's a 3-month course built to elevate your AI skills and land you a job doing your magnus opus project.

Physical Classroom

Learn in person through real conversation and interaction with your teachers.

Real Projects

Implement deep skills into a real proof-of-concept project.

Career Support

Get career advice from your mentor, get support from our in-house placement expert.

The AI Deep Dive curriculum works in 2 blocks that are designed to get you job-ready.

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Hard skills are critical, but they also need to be deployable in order to be relevant.

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Classes by experienced professionals that will get you up to speed as an AI practitioner. You'll gain a deep understanding of the essential concepts while working on exciting, real-life tasks.

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In the second block, the training wheels falls off, and you'll be working on your own project. We'll help you decide on a new application that showcases your expertise.

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We'll guide you through the process of developing with an impressive final product to show the world: your personal portfolio.

about us

Frequently Asked Questions

The tuition fee is CAD 15,000.

To date, 100 % of our graduates find their job within six months of graduating; 85% within three months. Connect to our graduates to know more; you can see the alumni (and their LinkedIn profiles) https://datascienceretreat.com/graduates/

  • Study Python, Machine Learning and Deep Learning. Online learning, such as Coursera, prepares you further for this endeavor. We look for a solid programming knowledge base in the participants we accept into the program.
  • Practice. Experiment with small projects.

Yes, for eligible participants.

You can certainly land a job by doing interviews remotely, however, being around helps your search because you can attend meetups, have lunch or coffee with potential employers and more. Staying for at least three months after the program ends is ideal.

Our program takes place on weekday evenings and Saturdays. 5:30pm - 10:30pm MON - FRI, 8am - 7pm SAT



Have more questions about AI Deep Dive?

Schedule a call, drop by in-class, or email Charlie, our Operations Manager.

Team Members

What if you could walk into a job interview and hand them a project like this?

Oil Prices Predictor
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    Christian Lübbe is a PhD in Math, Lecturer at the University of Oxford and a participant of Data Science Retreat, Batch 14. His project at DSR aimed at "Predicting the petrol prices in Germany".

Check it out
Self-Driving Car
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    Marcus Jones in an Engineer and Physicist from Canada who has been working in the field of energy and sustainability. The self-driving car detects paths, and autonomously drives along them.

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Skin Cancer Diagnosis
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    Dr. Juliana Du is a PhD in Human Genetics. She enrolled at DSR as part of Batch 13, and ended up building an app that uses computer vision to diagnose melanoma in humans.

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Fake News Detector
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    Diego Amicabile has worked across Europe in the IT industry for nearly two decades before coming to Data Science Retreat's Batch 12 and working on a fake news detector to expose fictitious news stories in the tech world.

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Gender Bias Detector
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    Carmen Iniesta enrolled in Batch 12 of Data Science Retreat, and produced a visual analyzer for gender bias found in the media, tech, and further afield in the hopes of mitigating those biases.

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Solar Energy Forecaster
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    Dr. Setareh Sadjadi is a Chemical Engineer who participated in DSR Batch 13. She wanted to produce a project relating to climate change and the promotion of renewable energy usage. She wrote a script to predict and forecast photovoltaic power from a solar-panelled roof.

Check it out

The AI Deep Dive curriculum works in 2 blocks.

Hard skills are critical, but they also need to be deployable in order to be relevant. The first block consists of classes by experienced professionals that will get you up to speed as an AI practitioner. You'll gain a deep understanding of the essential concepts while working on exciting, real-life tasks.

In the second block, the training wheels falls off, and you'll be working on your own project. We'll help you decide on a new project that showcases your expertise. We'll guide you through the process to finish off with an impressive final product to show the world: your personal portfolio.

Our Curriculum Overview

Foundations of Classical Machine Learning
Estimated time: 15 Hours

While deep learning has essentially become the benchmark for unstructured data, businesses still have plenty of use cases for classical machine learning. Particularly with regards to tabular data. AI Deep Dive participants have a solid knowledge base, therefore classical machine learning is covered beyond the introductory level.

  • Bias & Variance Trade-Fff

  • Norms & Distances

  • Scaling & Outliers

  • Gradient Descent

  • Homogeneity Metrics

  • Decision Trees

  • Support Vector Machines (SVMs)

Data Wrangling at Scale and Command Line
Estimated Time: 40 Hours

Large ever-changing datasets needed a new paradigm: we are not dealing with tables, but with streams. This is the realm of Kafka, Spark Streaming, Flink, and more. Additionally, we look at best-practice SQL, Scikit-Learn pipelines, and contemporary geodata handling to give participants a robust foundation for data wrangling.

  • Scikit-Learn Pipelines

  • Geodata Handling

  • SQL for the 21st Century

  • Kafka, Spark Streaming

Computer Vision with Deep Learning
Estimated Time: 50 Hours

We will cover a few Convolutional Neural Network (CNN) architectures that have made a big splash in computer vision, such as Inception, VGG16, and ResNet. Many portfolio projects at AI Deep Dive use CNNs due to their impressive results, and computer vision makes for vibrant demos. The architecture we include will depend on the state of the art.

  • Fundamentals of Computer Vision & Image Processing

  • Object Detection & Image Segmentation

  • Applications & Trends in Computer Vision

Soft Skills, Case Studies, and Technical Communication
Estimated Time: 33 Hours

The world of Deep Learning and AI is changing rapidly and it is not enough to just have the skills and competence: you also need to know how, when, and where to use them. To maximize your career trajectory, you need to identify areas where you can leverage your unique skills to maximum effect. Part of our goal with the program is to give you hard skills, but also the soft skills necessary to navigate this climate.

  • Business Case Studies

  • Soft Skills, Interview Skills, and Negotiation

  • Technical Communication & Demo Day Rehearsal

Natural Language Processing
Estimated Time: 71 Hours

This course will provide an introduction to Natural Language Processing (NLP). The focus of this course will be on the development of Machine Learning and Deep Learning models for a variety of use cases like sentiment analysis, Named Entity Recognition (NER), clustering, recommendation, classification, translation, generation, and summarization. The participants will gain hands-on experience with professional tools and techniques, and Python libraries such as TensorFlow, NLTK, and spaCy.

  • Working with text and natural language data.

  • NLP in Python, using common libraries such as NLTK and spaCy.

  • Assessing, transforming, and selecting the appropriate features for building machine learning and deep learning models.

  • Explaining Machine Learning and Deep Learning concepts of an NLP ecosystem.

Creative Portfolio Project
Estimated Time: 250 Hours

This is where it all comes together. You will deploy your hard skills on a creative portfolio project with the help of your mentors. The goal here is to solidify your command of AI hard skills in a way that no online program can.

  • We will assist you in finding a project that helps you brand yourself as an Data Scientist & Machine Learning Engineer.

  • You will apply the skills that you have developed during the course to ensure a high quality project.

  • You will work closely with your mentors over the course of the project.

  • You will present your project to the public on "Demo Day".

Meet Our Alumni

These are just a few of the hundreds of students who have graduated from our program in the past 6 years.

Team Members
Lisa Hesse
Deep Learning Scientist

Lisa Hesse

Before: Posdoctoral Research Scientist

After: Deep Learning Engineer

Team Members
Toavina Andriamanerasoa
Senior Data Scientist

Toavina Andriamanerasoa

Before: Finance Professional for Marlborough Partners & Houlihan Lokey

After: Senior Data Scientist

Team Members
Roberto Bruno Martins
Machine Learning Specialist

Roberto Bruno Martins

Before: Business Intelligence Manager

After: Machine Learning Specialist

Meet Our Mentors

Our mentors are leaders in their field.
Our team of mentors comprises of Principal Data Scientists, Researchers, and Kaggle champions.

Team Members
Krista Bennatti-Roberts, CPA, CA
Data Scientist

Krista Bennatti-Roberts, CPA, CA

Krista is a Data Scientist at Hansell McLaughlin Advisory Group, a boutique law and advisory firm specializing in corporate governance. Her role encompasses NLP, statistical modelling and process automation. Krista's work on corporate governance and financial regulation has been featured by the Harvard Law School Forum, by The Conference Board, and others

Team Members
Lucas Durant
Data Science Tooling Lead at TD Securities

Lucas Durant

Lucas got his start in Finance 6 years ago, when he broke away from years of study in Physics to take a seat on the trading floor of a major Canadian bank. He has taken on a number of roles in the Fintech space as part of the TD Technology Solutions Associate Program, with the majority of his time spent developing computational financial models with Quant teams in retail and wholesale banking, as well as implementing Big Data and Machine Learning solutions with a focus on leveraging Python to unlock analytic power for the user.

Team Members
Subash Gandyer
Data Scientist at Healthchain

Subash Gandyer

Subash Gandyer is a seasoned AI/ML practitioner with 5+ years of experience. Currently working as a Data Scientist in a Healthcare Startup. He taught Computer Science, Machine Learning, and Deep Learning to University students in India for 9+ years. When he is not building deep models, you can see him dancing at jive and salsa parties.

Team Members
Palak Trivedi
Technical Consultant at Advanced Utility Systems

Palak Trivedi

Presently working as a Technical Consultant in a Toronto based IT company where she is involved in managing multiple projects, from gathering requirements to implementation. She holds a master's degree in Computer Application. She has spent 8+ years teaching undergraduate and graduate students in Computer Programming and has also worked as a Corporate Trainer for Microsoft certification courses. She has coordinated more than 50 dissertation projects for final year students. With significant experience in the field of database (design, normalization, reporting, Transact-SQL, ETL Tools, and more), she is well-versed with the software development life cycle model for each project to enhance and improve information systems.

Team Members
Alexander Tedeschi
Data Scientist at Uber

Alexander Tedeschi

Alex works at the cross-section of GIS, Data Science, and Urban Planning at JUMP - a fast-growing bike and scooter-sharing startup acquired by Uber 1 year ago. A recent graduate of DSR, Alex took part in a group project that applied computer vision to detect whether bikes are properly locked on the street. He holds a Master of Science in Geoinformatics from the University of Münster in Germany and a Master of Arts in Regional Studies of Russia, Eastern Europe, and Central Asia from Harvard University. Before delving into the field of shared mobility, Alex interned at one of Russia's leading Urban Planning firms - KB Strelka - where he helped develop resources for spatial information management and designed maps for MyStreet, a large scale, ongoing urban renovation project in Moscow. In addition to being an Urbanist, Alex has a passion for history and has volunteered as a cartographer with Memorial, a human rights NGO that illuminates human rights violations in the past and present.

Team Members
Jay Dawani
Lemurian labs, CEO

Jay Dawani

Jay is Founder and CEO of Lemurian labs (and has leadership roles in 2 other companies). He has provided consultation to diverse companies, including SpaceX. Jay got into AI at the age of 14; received world distinctions in Mathematics and Physics from Cambridge for his top marks. Jay is currently authoring a book - "Mathematics for Deep Learning." Jay is part of Forbes' 30 Under 30.

Team Members
Jose Quesada, PhD
AI Deep Dive, CEO

Jose Quesada, PhD

Jose is the Founder and CEO of AI Deep Dive (Toronto) and Data Science Retreat (Berlin). Jose has mentored and directed over 165 Machine Learning portfolio projects. Some resulted in startups; others ended up being non-profits with significant social impact. His goal is to demonstrate that a single person or small team can have an enormous impact thanks to open source and pre-trained models. One doesn't need to be a big corporation to solve the world's worst problems with technology.

Team Members
Pooja Bhojwani
Data scientist at Scotiabank

Pooja Bhojwani

Pooja Bhojwani is a Data Scientist working with the Fraud Detection Group at Scotiabank, a leading commercial bank with subsidiaries in Canada and South America. In her daily job, she employs state-of-the-art Machine Learning techniques and statistical analysis to protect Scotiabank and its clients against various financial threats. She completed her Master's in Computer Science at University of Victoria in 2018 and has more than 3 years of industrial experience.

Team Members
Devang Swami
Consultant, BI Developer at CGI

Devang Swami

Devang Swami is a data engineering and deep learning expert. He works as a BI Developer - Consultant and helps his client build and optimize data platforms for Machine learning/AI tasks. He is proficient in a multitude of Big data platforms like Hadoop Ecosystem, Spark, Kafka, and many NoSQL databases. In his free time, he works on developing deep learning models Self-driving cars using camera and LIDAR sensors.

Team Members
Saby Dasgupta
Senior Data Scientist at Loblaw Companies

Saby Dasgupta

Sabya works as a Senior Data Scientist with expertise in developing data driven solutions to drive business value. Graduated with a Masters from IIT Bombay & Ph.D Univ. of Cologne, Germany trained as a theoretical physicist remains passionate towards exploring quantitative features of large-scale data using iterative model building and data visualization via. scalable technologies . Sabya works as a Senior Data Scientist with expertise in developing data-driven solutions to drive business value. Graduated with a master's degree from Indian Institute of Technology Bombay & has a PhD from University of Cologne, Germany. Sabya was trained as a Theoretical Physicist, and remains passionate towards exploring quantitative features of large-scale data using iterative model building and data visualization via scalable technologies. Loves to help others learn, build synergistic teams to facilitate streamlined exchange of knowledge, leveraging 10+ years of experience across 3 continents.

Team Members
QINGCHEN WANG​, PhD.
Assistant Professor / Data Scientist

QINGCHEN WANG​, PhD.

Qingchen is an award-winning Data Scientist with rigorous training in Machine Learning, Artificial Intelligence, Statistics, and Econometrics. He is one of only 87 grandmasters (as of mid-2017) on the Kaggle Data Science competition platform (top rank of 14th out of 52,000+ active competitors on Kaggle), and has significant experience in Software Engineering (C++, Java, Python). He is currently working on research and development for data-driven solutions to problems in Digital Marketing.

Team Members
KELVIN LWIN
AI Architect

KELVIN LWIN

After spending nearly a decade at UC Berkeley, Kelvin decided to repay his debt to the public education system by helping build UC Merced. He spent 7 years teaching 4,500 students across 55 classes, while redesigning the undergraduate Computer Science curriculum. He is currently designing curricula at NVIDIA’s Deep Learning Institute (DLI) to democratize access to the latest technologies across many disciplines, industries and geographies. Kelvin helped DLI reach over 100K Developers worldwide, directly and in collaboration with Udacity and Coursera/Deeplearning.ai. He continues to search for ways to leverage AI to solve the paradox of progress.

Meet Our Team

Our mentors are leaders in their field.
Our team of mentors comprises of Principal Data Scientists, Researchers, and Kaggle champions.

Team Members
Jose Quesada, PhD
AI Deep Dive, CEO

Jose Quesada, PhD

Jose is the Founder and CEO of AI Deep Dive (Toronto) and Data Science Retreat (Berlin). Jose has mentored and directed over 165 Machine Learning portfolio projects. Some resulted in startups; others ended up being non-profits with significant social impact. His goal is to demonstrate that a single person or small team can have an enormous impact thanks to open source and pre-trained models. One doesn't need to be a big corporation to solve the world's worst problems with technology.

Team Members
Subash Gandyer
Data Scientist at Healthchain

Subash Gandyer

Subash Gandyer is a seasoned AI/ML practitioner with 5+ years of experience. Currently working as a Data Scientist in a Healthcare Startup. He taught Computer Science, Machine Learning, and Deep Learning to University students in India for 9+ years. When he is not building deep models, you can see him dancing at jive and salsa parties.

Team Members
Charlie Galipeau
Head of operations

Charlie Galipeau

Charlie Galipeau develops, implements and reviews operational policies and procedures for AI Deep Dive. She oversees budgeting, reporting, planning, and auditing. Charlie is passionate about promoting a company culture that encourages top performance and high morale.

Have any questions about AI Deep Dive?

Schedule a call or email Charlie, our Admissions Manager, who will help you think through the decision.

Team Members