BIG DIVE Module 2

Machine and Deep Learning intensive

From October 12 to October 16

This immersive week is aimed at pushing forward Machine Learning and Deep Learning skills in the specific field of Computer Vision. It starts with a Machine Learning introduction and application with Scikit-learn, and continues with advanced Neural Networks and backpropagation lectures where you’ll start exploring Computer Vision techniques on a dataset of images.

You’ll receive a boost in Deep Learning methods by using TensorFlow and Keras on a image classification real cases. 

The workshop ends with lessons in Transfer Learning and one last project building your data set by scraping Google images and practicing everything you learned.

Deep teamwork sessions and top-value lectures by sector experts and top Data Scientists will complete and enrich this module.

Scientific Approach PerformancesOptimization PredictiveAlgorithms Data Exploration& Preparation CommunicationValue VisualRepresentation Deploying Data Pipelines Maths & Stats Coding

About Machine and Deep Learning

Machine Learning is the sub field of Artificial Intelligence devoted with mining patterns and extracting knowledge from data, especially when said data is abundant but unstructured.

Nowadays, the vast availability of data and lowering hardware cost has led to the application of ML techniques to a wide variety of domains, spanning from healthcare to advertisement, from finance to fashion – with the consequent consolidation of the Data Scientist role.

A solid, hands-on understanding of ML principles and tricks of the trade allows data scientists to work in an ever-growing number of application domains.

Deep Learning is a specific set of ML tools that in recent years has emerged as state-of-the-art approach for tackling complex problems, such as computer vision or natural language understanding, thanks to their ability to automate feature engineering. DL is arguably the bleeding edge of modern Artificial Intelligence, and yet high-abstraction libraries such as TensorFlow and Keras allow to train neural network and develop prototypes with concise and elegant code. This module will focus on convolutional deep neural networks for computer vision, as this is the keystone for many modern technologies and services.

Is this course for me?

This advanced course is perfect for people with a solid Python language knowledge and a robust background in math and stats.

The course is perfect for data analysts, junior data scientists, data engineers that want to acquire ML/DL skills, Python developers, and PhD students who want to prove themselves in the real world.

We will ask you to fill out a questionnaire/Jupyter Notebook to test your skills. By attending BIG DIVE Module 1 “Python for Data Science and Machine Learning”, you will have all the necessary prerequisites.

Syllabus and teachers

BIG DIVE for Machine and Deep Learning will cover

  • Introduction to Machine Learning and Data-Driven projects
  • Overview of ML tasks and hands-on sessions on ML algorithms with Sklearn
  • Statistical Learning Theory – with practical exercises!
  • Neural Networks and Backpropagation
  • Building from scratch and training neural networks with TensorFlow and Keras
  • Brief history of Deep Learning, with focus on Computer Vision
  • Building from scratch and training deep convolutional NNs with TensorFlow and Keras
  • Transfer Learning: feature extraction and fine-tuning
  • Group project

This session will also include:

  • Lectures by experts
    • Kaggle challenges by Aberto Danese, Kaggle Grandmaster and Head of Data Science at Nexi
    • Machine Learning and forecasting in Glovo by Matteo Giaretti, Glovo
  • Hands-on sessions and group exercises to put in practice the lessons learnt

Resident teachers and coordinators:

André Panisson
Research Leader at ISI Foundation | Data Science Lab

Alan Perotti
Artificial Intelligence Researcher and Data Scientist

Stefania Delprete
Data Scientist at TOP-IX

Nicola Occelli
Engineer at TOP-IX

Christian Racca
BIG DIVE Program Manager

Are you interested in attending more than one BIG DIVE training module and becoming a Data Expert at 360°?
Look the other modules and leverage the discount package!

From Zero to Data Science with Python (beginner class) – September 2020
Communicating and Visualizing Data (beginner to intermediate class) – November 2020
Deep Dive into Data Engineering (advanced class) – December 2020

Application process

Here’s a timeline of what will happen:

February 17 Registrations opening
May 31
Early-bird expiring
October 4
Registration closing
From Oct 12 to Oct 16
BIG DIVE Python for Data Science and Machine Learning

The application process starts with a self-evaluation of the prerequisites (mostly related to your programming skills and Maths background) needed to access and fully enjoy the course. Optional skills were taken into consideration to create a balanced classroom. You can download here a preview of the questions and requirements of the official application form.

In the form, you can tell us more about you, your previous experiences and why we should choose you. We strongly encourage you to make a short video to stand out among the other candidates!

We will ask you to fill out a questionnaire/Jupyter Notebook to test your skills. By attending BIG DIVE Module 1 “Python for Data Science and Machine Learning”, you will have all the necessary prerequisites.

After we receive the applications our team starts the screening. Candidates might be contacted by the organizers and asked to provide more information about skills or to attend an interview (in person or using a remote audio-video communication tool). The selection process continued till the official registration closure to create progressively a class of a minimum of 8 and maximum 20 Divers.

Applicants selected before the official end of registration were asked to pay a deposit (40% of the total due fee – according to the profile). In case of missing deposit (deadline is one week after the request) the candidate loses the priority in the selection queue. In case a selected candidate renounces to participate, a new Diver is selected. The deadline for asking for the deposit refund is fifteen days before the course begins (we do not refund unused portions of the training).

If you purchase more than one module, the deposit amount, payment deadlines and refunding options will be discussed and communicated privately.

All the news about selection, exclusion and deposit request are communicated by email through the email address inserted in the application form.

Logistics and technical information

From Monday to Friday from 9:30 am to 4:30 pm. Additional time was reserved for special lectures, exercises and “homework”.

One day of absence is allowed on a total of five training days.

Venue: TOP-IX headquarters in Torino (Via Maria Vittoria, 38).

Technical prerequisites: bring with you your laptop (GPU-laptop are welcome). We will preferably use an online environment (JupyterHub or Colab) but you are free to use your local Python working environment (the required libraries and packages versions will be communicated in advance).

Training language: English.

Accommodation, food and travel: these expenses are not included in the course fee. We will send you some recommendations (how to stay, where to eat,…) based on our experience.

Organizer and partners

BIG DIVE 2020 is organized by:

In collaboration with:

AXANT    ISI Foundation & ISI Global Science Foundation   TODO Creative Agency

With the patronage of:

Dipartimenti di informatica Università di Torino

A pleasure not only for the mind…

The venue for the course is a recently renovated space in a beautiful historical building in the center of Turin close to the river.

Turin is one hour from the Alps and two hours from the seaside.

By train you can easily traveling among Milan, Florence, Rome, Venice to celebrate after (or during) the BIG DIVE 2020 with your classmates!

Check the frequently asked questions

A copy of your University ID card or any certificate proving you are a student at the time of application. You can send it at after you filled up the form online.

A good background in Statistics, Python and its basic data science libraries (pandas, NumPy, Maplotlib, Seaborn) are mandatory. If you will apply for this module you’ll be asked to fill out a questionnaire or Jupyter Notebook to test your skills.

Remember we will preferably use an online environment (JupyterHub or Colab) but you are free to use your local Python working environment (the required libraries and packages versions will be communicated in advance). A GPU-laptop is recommended.

As BIG DIVE will be taught in English, proper conversation and writing skills are required.

Please write us to for any clarifications.

You video is strongly suggested for selection purposes,  the letters of recommendation are not mandatory.

We encourage you do add them to your application to get know you and your motivation better and better evaluate your profile.

The course is designed to be fully-attended in Turin, Italy.

Yes, at the end of this course you’ll receive a certificate of attendance if you take part at more than 85% of the lessons and activities.

As this year BIG DIVE 2020 is divided in four modules, you’ll receive one certificate for each module you would decide to attend.

Yes, you can download a courtesy application form in PDF on this link.

It includes the full list of questions and requirements.

Yes, from this link you can download a PDF of BIG DIVE 2020’s pamphlet here.

It can be useful to be shown to different department in you organization.