Open programmes

School of Artificial Intelligence

School of Artificial Intelligence

Become an AI expert through our hands-on mentoring programme, working on real industry projects.

Twice a year, we host a batch of the best engineers from all over the world to turn them into AI specialists. Each of them receives personalised coaching and guidance from an expert. They apply their new skills on the industry project provided either by their own employer, or by world leading tech companies such as Google, Facebook and Amazon and fast-growing startups.

Merit First. Top developers get in for free, and those who transfer from abroad will receive a travel and accommodation grant.

Learn by doing. Minimal teaching. Desks and environment are organised to support small project teams, agile co-development, interactions with mentor.

Real world projects, no simulations. Our partners sponsor top developers to solve real challenges. This may convert into the best job you ever had.

About this programme

  • Start date April 2018
  • Application deadline March 2018
  • Duration 8 weeks full-time
  • Audience Skilled developers
    with little to no AI experience
  • Cost 15,000 €
    15 full grants available
  • Location Pi Campus, Rome
Apply now for a full grant

Outcomes

Enter the world of AI through the front door

Engage with thought leaders from top industry and research groups

Get expert advice on your own project

Gain expertise

Programme director


Sébastien Bratières

Director of AI, Translated

Sébastien has over 15 years of experience in the AI industry, covering topics ranging from speech interfaces and chatbots to data science. He has taught both professionals and students at institutions including École Centrale Paris and LUISS Business School in Rome, and consistently receives glowing reviews from his pupils. He carried out his PhD in probabilistic machine learning at the University of Cambridge, home to one of the world’s leading research labs. Sébastien is a regular speaker at international events dealing with machine intelligence.

The programme director will be available at all times to:

  • define your strategy
  • recommend resources, libraries
  • fill knowledge gaps
  • help when you get stuck
  • … and challenge you when you’re low on energy!

Advisory Board

Our advisory board is here to make sure that every single project is based on bleeding edge technology. Simply put, they make sure there’s no better way to do it.

Alex Waibel

Professor of Computer Science

A pioneer in neural network speech recognition, Alex invented time-delay networks in 1989 as part of his PhD at CMU, having previously graduated from MIT with a BSc in 1979. In addition to his academic career, he has co-founded 10 successful commercial ventures. One of these, Jibbigo, was acquired by Facebook in 2013, leading Alex to found Facebook's Language Technologies group. He has received more prizes and distinctions than we have space to list here, and is a fellow of the IEEE and a member of the German Academy of Sciences.

Hassan Sawaf

Director of AI, Amazon Web Services

After completing his PhD at RWTH Aachen, Hassan started off as a researcher, but quickly branched out and set up a speech-to-speech translation company. He has served as a CEO or Chief Scientist for several ventures in the speech recognition industry. He joined eBay in 2013 and became Head of AI before leaving to head up Amazon's AI efforts. He is now Director of AI at AWS. Hassan serves as a board member and advisor for a number of AI companies which he helped to found, including Witlingo and Gyant. Hassan also makes angel investments through Keiretsu.

Marcello Federico

Head, Human Language Translation Unit

A pioneer in the field of machine translation, Marcello’s research focuses on methods to integrate human and automated translation. Marcello is the co-founder and scientific advisor of MateCat and ModernMT, a project which aims to deliver real-time domain-adaptive neural machine translation. Marcello has co-authored over 180 scientific publications on machine translation, language modelling, speech recognition and information retrieval. He has been a committee member at all the major international industry conferences and is also a senior member of the IEEE and the ACM. Marcello graduated “summa cum laude” from the University of Milan in 1989.

Mentors

Our mentors are AI engineers from the industry's finest labs.
Alongside the Programme Director, they will coach the students on a weekly basis.

Lukasz Kaiser

Researcher, Google Brain

Lukasz’s research focuses on deep learning applied to natural language processing, and he has recently been working on the use of attention models and transfer learning. Lukasz is a key contributor to Tensor2Tensor, an open-source TensorFlow library containing implementations of several state-of-the-art neural models. He earned a PhD from RWTH Aachen in 2008 and Master’s degrees in mathematics and computer science from the University of Wroclaw in 2003.

Adam Gibson

Founder & CTO

In 2013, Adam co-founded Skymind, the startup which produces the open-source Java deep learning framework Deeplearning4j and ND4J (n-dimensional arrays). A year later, he left his computer science studies at Michigan Technological University to work on Skymind full-time, raising money from Y Combinator and Pi Campus. Adam wrote “Deep Learning: A Practitioner’s Approach”, published by O’Reilly in August 2017, and he also is an advisor to the data science master’s program at GalvanizeU in San Francisco.

George Tall

Co-founder & CTO

George founded lvl5 (precision maps for self-driving cars) with ex-Tesla engineers Andrew Kouri and Erik Reed while he was studying towards his MS in computer science at Georgia Tech. Before this, he was on iRobot's Advanced Development group where he worked on monocular-visual and volumetric SLAM algorithms. George received a BS in mechanical engineering (with a concentration in computer science) from Northwestern University in 2013.

Denny Britz

WildMl writer
former Google Brain

Denny Britz was a resident on the Google Brain team where he worked on NLP problems such as Machine Translation, Conversational Modeling, and Summarization. He studied Computer Science at Stanford University, working on probabilistic models for Information Extraction, and UC Berkeley, where he worked on a popular cluster-computing framework called Spark. He started the blog WildML to share his excitement about Deep Learning with the strong belief that writing posts and tutorials is the way to deepen the knowledge.

More to be announced

We're currently in touch with several more machine learning scientists and practitioners who would like to mentor our students. Stay tuned

Want to join?

  • Candidate

    Are you a student or AI enthusiast? Apply for one of our fully-sponsored places and give your career in AI a boost. Or if you're employed, convince your company that training in machine learning and AI is the best investment they can make these days. You'll be mentored by some of the finest minds around, representing institutions such as Cambridge, Google, Facebook, Amazon, Carnegie Mellon and more. All while gaining hands-on AI and machine learning experience and specialist skills by working on your sponsor company’s industry project.

    Apply now for a grant

  • Enterprise

    Unlock the potential of machine learning for your business projects and train your engineers at the same time. Work with our Director to develop your project into a specific machine learning concept with clearly defined deliverables. Maximise the value of your training by opting for a programme based on mentoring and individual sessions. We guarantee that the intellectual property rights and confidentiality of your data and results will be protected.

    Apply now

    Download the brochure (PDF, 4 MB).

  • Partners

    Associate your brand with the cutting edge of AI. Sponsor scholarships for bright students taking part in our hands-on AI training course. Create your own data science or AI c hallenge for the trainees you sponsor to work on. Name a recipient for your scholarship, or let us find and select the most deserving. All our supporters are featured in Pi School's online and offline communication and invited to our networking events.

    Apply now

    Download the brochure (PDF, 4 MB).

Schedule

Before
Are you an enterprise? We will consult with you for one or two days to scope out your AI project for the training programme format
Weeks 1-2
Programme introduction and “Essentials” lectures
Weeks 3-8
Project work, personalised training, tutoring and mentoring, group activities
Week 8
Project presentations and final event
After
Recruitment opportunities with our partners.
Alumni events at Pi Campus.

Areas we cover

Deep learning
Gesture recognition
Text and document processing
Big data systems
Data collection and generation
Speech, sound, image, video processing
Time series
Recommendation systems

Connecting Dots

Pi School is part of Pi Campus, which is located in Rome, Italy.

Pi Campus is both a venture capital fund and a startup district; it invests in growth-stage startups, with 28 investments in Italy and worldwide, and hosts some of them. Pi Campus was co-founded in 2007 by Marco Trombetti, a serial entrepreneur and angel investor, based on the commercial success of his first venture, Translated, an online translation platform which he co-founded in 1999.

Pi School offers professional education programmes and bespoke courses in its two specialist areas, which are also the cornerstones of Pi Campus: innovation, creativity and design alongside AI and machine learning.

Pi School is led by Jamshid Alamuti, an expert on innovation and leadership, but above all a transformer and people development expert. Jamshid formerly transformed and led the Berlin School of Creative Leadership and designed and ran many other educational institutions in Europe, where he developed EMBA units and C-level programmes. in between, Jamshid has always been an independent leadership consultant, speaker and writer in order to keep the balance between theory and practice. He co-founded Pi School with Marco Trombetti in 2016.

FAQ

Requirements

We run the programme in English, so you must be able to work in English.
You must have a formal STEM background in a quantitative discipline (yes, machine learning uses maths!). You must know how to code, preferably in Python, which is the de facto standard programming language for AI and data science.
We have no specific requirements about your knowledge of machine learning or AI, but obviously it won’t hurt if you have some prior exposure, through a MOOC, a workshop or an individual project. Because our training is totally personalised, the further along you are already, the further we’ll take you.

Grant selection process

If you’re a great developer, our partners are interested in sponsoring you. We will award grants following a selection process based on a CV, a 300-word cover letter, and two technical video interviews lasting an hour each (focusing on engineering skills rather than AI).

Do I have to stay on-site for the entire 8 weeks?

We recommend that you stay for the whole 8-week programme to reap the maximum benefit, not just from the lectures and mentoring sessions, but also from informal networking and exchanges around Pi Campus.
Under special circumstances (e.g. family or professional reasons), you may attend part of the programme remotely, except for the first 2 weeks, for which you must be on-site.
If financial reasons (e.g. accommodation and maintenance) would prevent you from attending, please contact us, as we have maintenance grants available.

What is included?
What is left for me to organise?

Need more info?

  • Want to join the programme as an enterprise?
    Ask our Programme Director:

    Download the brochure (PDF, 4 MB).

    Sébastien Bratières - Programme Director