Your path to excellence in the realms of Artificial Intelligence & Cloud

2nd level Specializing Master's Programme from Politecnico di Torino, coordinated by Reply and aimed at young talent.

Artificial Intelligence & Cloud – Master’s Degree

Hands-on Innovation

It is a unique programme, recognized by MIUR (Ministry of Education, University and Research) and developed in collaboration with Politecnico di Torino, to offer an elite group of highly qualified students a professional specialization in the most innovative fields of the IT sector.

The first edition of the Master’s programme on Artificial Intelligence and Cloud is scheduled to start in January 2021 and a maximum of 40 students will be admitted. The course will be taught in English and is expected to have a duration of one year at Politecnico di Torino’s campus and in Reply’s offices.

Who is the Master’s aimed at and why enrol?

The 12-month programme is aimed at the most talented students with a degree – including those who will obtain their degree by 31 December, 2020 – in Computer Engineering, Computer Science, Automation Engineering, Telecommunications Engineering or Electronic Engineering.

Are you a talented student?
We invest in your talent and the Master’s is free for you!

Reply are committed to hiring all of the admitted applicants and to sponsor the entire programme for those who accept the job-offer and agree to stay for 2 years from the end of the course.

Is this not enough?
For one year you earn, while you learn, and you get a job too!

#EarnWhileYouLearn

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Key Info

Target

Completed degree by 31 December, 2020 – in Computer Engineering, Computer Science, Automation Engineering, Telecommunications Engineering or Electronic Engineering

Deadline exstension!

2 November, 2020 – 13:00 (CET)

Participants

40 selected

Cost

Reply will cover the participation fee (18.000 €) if you’re selected for the programme and you accept the Reply job-offer

Recruitment and career

Reply will hire the admitted applicants who accept the job-offer and commit to stay for 2 years from the end of the Master’s programme

Time schedule

1 year, from January to December 2021

Didactics

6 months of Class-based training + 6 months of On-the-job training and thesis

Language

English

Where

Politecnico di Torino campus and Reply’s offices

The timeline of the initiative

Base Courses

Specialisation

Project Work

Thesis

What will I learn by completing this Master’s?

An in-depth knowledge of the technologies that are at the basis of the major transformations taking place in all product sectors.

An understanding of how these technologies can be adopted in practice to solve real-life problems.

A specialisation in one of three key areas: Cloud, Data or Machine Learning.

An awareness of how these technologies are made available by major platform providers and the differences between them.

The Reply methodology: to learn from our professionals based on a practical approach, adopting a distinctive working method focused on excellence and collaboration.

Specialisations to choose from

The Master’s in Cloud, Data and Machine Learning illustrates how to use modern digital technologies in practice: from effective data management to the adoption of Artificial Intelligence and Machine Learning techniques, all through the latest Cloud-based implementation models. The Master’s follows three areas of specialisation, which the student will be able to choose from:

Cloud

Within the Cloud specialisation, the Master’s will explore a number of the main components that characterise IaaS and PaaS solutions. The following three topics will be covered in particular:

The main methodologies and technologies that facilitate the DevOps approach:

DevOps principles
The main processes (Continuous Integration, Continuous Delivery and Deployment, Rugged DevOps / DevSecOps, ChatOps, Kanban) and their relationship with IT Service Management
Open Source Technologies for Configuration Management: Puppet, Chef
AWS Cloud-native DevOps techniques

Microservice-based architectures. Containerisation in the delivery of hybrid Cloud architectures: Docker, Kubernetes, Openshift

The design of a microservice architecture
Management of microservice architectures
Continuous Integration and Continuous Delivery (CI/CD) in containerised architectures
Cloud Native microservice architectures: serverless (AWS)

Serverless development

Main PaaS services
An example of a Serverless project: IoT architectures backend

AI: Data

Within the Data Management specialisation, students will study, in depth, the technologies and methodologies that enable the adoption of a data-driven approach.

From a Data Engineering point of view, the following topics will be covered in particular:

The technological origins of Big Data: Hadoop, MapReduce, Hive, Spark, Cloudera, etc.
Main data architectures: Lambda Architecture, Kappa Architecture, event-driven, CQRS, data mesh
Options for modelling relational data: Data Vault 2.0, the Snowflake schema, the Star schema
Components for managing real-time contexts: Kafka, Spark Streaming, Akka Streams, Flink
Options for storing large volumes of data: NoSQL (MongoDB, Cassandra, Redis, etc.) and indexers (Elasticsearch, Solr)
AWS Cloud-based, data platforms
The impact of containerisation in the data context: Docker, Kubernetes, Openshift

The following topics will be covered from a Data Science point of view:

Descriptive analysis: The study of the normal distribution of data through metrics such as the mean, variance, standard deviation and percentiles. The application of statistical tools such as hypothesis tests and p-values, to extract information about the distribution of the data
Classification algorithms (supervised), models: Logistic Regression, Random Forest, Evaluation Metrics: accuracy, precision, recall
Clustering algorithms (unsupervised): Kmeans, Hierarchical Clustering
Recommendation algorithms: Content Based, Collaborative Filtering
Text mining and Natural Language Processing (NLP): unstructured text analysis, both in the cleaning phase (lemming, stemming, tokenisation) and in the model phase (sentiment analysis, text classification)
Data Science Tools: focus on Jupyter and Anaconda for Python code development with Jupyter Notebooks support
Data visualisation: Python packages for Seaborn, Matplotlib exploratory analysis

AI: Machine Learning

This area of specialisation focuses on the use of leading Artificial Intelligence and Machine Learning techniques such as image and video intelligence, text analytics, language understanding, predictive systems and reinforcement learning, as well as on an in-depth study of the cognitive systems offered by one or more of the leading industry vendors (AWS, Google, Microsoft, etc.) and the application of these in multiple contexts of use such as Autonomous Things, Digital Assistants, Predictive Maintenance, Intelligent Process Automation and Smart Analytics.

The specialisation is characterised by a strong, hands-on component, which sees the involvement of participants in real-life projects using platforms and frameworks offered by leading industry vendors.

The implementation of state-of-the-art algorithms and models, the application of Deep Learning techniques and an in-depth look at Automated Machine Learning tools will go hand in hand with an approach aimed at capitalising on the results achieved with the definition of evaluation metrics for the effectiveness of the solutions developed from an enterprise perspective.

Who will guide me during the learning process?

The scientific committee

The Scientific Committee, made up of members of Politecnico di Torino and Reply Group professionals, was responsible for designing the training programme and is supervising the initiative.

Politecnico Instructors

The Master’s teaching staff is made up of professors and researchers from Politecnico di Torino, experts in the topics covered, who will guide you through this academic experience.

Reply Instructors

Reply’s professionals will take turns in teaching, in supporting laboratory activities and in serving as mentors to students during the project work, as well as during the preparation of their thesis. They will also give lectures on a number of cutting-edge subjects such as Quantum Computing and Blockchain.

FAQs

How much does the Master’s programme cost?

Where will the programme take place?

When does the programme start?

How can I apply for the Master course?

Is the programme delivered in person or online?

How many students will be on the programme?

Can I apply if I haven’t graduated, yet?

Do I qualify for the programme?

There are minimum admission requirements to apply for this programme:

you’ll need confident English language skills (B2)
you’ll need one of the following degree classes:
- LM-32 Computer Systems Engineering
- LM-18 Computer Science
- LM-25 Automation Engineering
- LM-27 Telecommunications Engineering
- LM-29 Electronic Engineering

You’ll also need to pass the interview stage.

You can find out more about the selection process on the Politecnico website.

How does the Reply job offer work?

Will Reply cover accommodation costs?

Is there an age limit?

What language is the programme taught in?

Is the Master’s programme full-time?

What equipment will I need?

Can I leave the Master’s programme before it’s finished?

Would you like more information?

For any further clarification you might require, write to us at

master@reply.com