Explore OPIT Courses

Dive into the comprehensive array of OPIT courses integral to our Master of Science (MSc) and Bachelor of Science (BSc) degree programs. This exploration offers a detailed overview of each course, highlighting their unique aspects and how they contribute to the broader educational objectives of the degrees.

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All the courses

Advanced Digital Marketing [Elective]

Professors

Description

In this module, students delve into a spectrum of strategies, ranging from SEO to AI-powered personalized marketing. Immerse yourself in the realms of social media, data-driven decision-making, and crisis management. Acquire proficiency in e-commerce optimization, PPC, and beyond. Enhance your skills through industry presentations and real-world challenges, guaranteeing success in the competitive digital landscape.

Agile Development and DevOps

Professors

Fabiano Lima
Fabiano Lima
IT Program Manager @ UBS, Certified PMP, PMI-RMP, CSM, PSM I, PSPO I, ITIL-F, Prince2, Agile. Location: Brazil

Description

The elective course in Agile Development and DevOps covers the principles, practices, and tools required for software development using the Agile methodology and DevOps culture. The course includes topics such as Agile project management, Agile software development, continuous integration, continuous delivery, containerization, automated testing, and infrastructure as code. Students will learn how to build software products in an agile manner, deploy and maintain them using DevOps practices, and manage the software development lifecycle with the help of various tools and techniques.

AI for IoT and Automation

Professors

Khaled Elbehiery
Khaled Elbehiery
Senior Director & Network Engineer @ Charter Communications, Professor @ DeVry University and at Park University. Location: USA

Description

This course explores the transformative synergy of Artificial Intelligence (AI), the Internet of Things (IoT), and automation. Students gain insights into AI's significance in IoT, types of sensors, edge computing, and integrating AI for automation. The module covers computer vision applications in IoT, video analytics, and real-world cases in smart cities, healthcare, and agriculture. It also addresses future technologies like Edge AI, 5G, and AIoT, considering ethical, privacy, and regulatory aspects.

AI in Business, Strategy, and Entrepreneurship

Professors

Moez Ali
Moez Ali
Founder and Creator @ PyCaret, Product Director - AI @ antuit.ai, Adjunct Lecturer @ Queen's University. Location: Canada

Description

In the digital transformation era, businesses and entrepreneurs explore unique opportunities with the integration of artificial intelligence (AI). This course explores AI's role in diverse business sectors, emphasizing strategy, leadership, innovation, and applications in supply chain optimization, financial analysis, marketing, and customer engagement. The module delves into entrepreneurship and AI startups, addressing legal and ethical implications through case studies and industry insights, preparing students for AI-driven business landscapes.

AI-Driven Forensic Analysis in Cybersecurity [Elective]

Professors

Description

This course focuses on the application of AI in cyber forensic analysis. It covers techniques to utilise AI-driven tools for faster and more accurate forensic investigations after security incidents.

AI-Driven Software Development [Elective]

Professors

Description

This course explores the transformative impact of Artificial Intelligence (AI) on software development. Participants delve into generative models, foundational in AI, understanding their role in software creation, improvement, and debugging. The curriculum blends theoretical concepts and practical applications, providing insights into leveraging Deep Learning techniques for generative models, specifically in Natural Language Processing (NLP). Topics include Generative Models, Deep Learning for NLP, Software Creation and Improvement, Debugging, and AI-Driven Testing.

Applications in Data Science and Artificial Intelligence - Part 1

Professors

Moez Ali
Moez Ali
Founder and Creator @ PyCaret, Product Director - AI @ antuit.ai, Adjunct Lecturer @ Queen's University. Location: Canada

Description

This is a thematic module showcasing applications of Data Science and AI tools to different fields e.g. drug design and drug discovery, physiological/physical analysis of athletes to improve performance, risk analysis in the insurance business, finance, and energy distribution optimization. The course will allow you to put into practice the knowledge, tools, and methodologies learned in the previous modules, by applying the to real-life applicative scenarios.

Applications in Data Science and Artificial Intelligence - Part 2

Professors

Paco Awissi
Paco Awissi
Vice President of Data and Reporting @ Morgan Stanley, Lead Instructor @ McGill University School of Continuing Studies. Location: Canada
Pierluigi Casale
Pierluigi Casale
PhD @ Universitat de Barcelona, Former Innovation Officer (Data Science and AI) @ European Parliament, Principal Data Scientist @TomTom. Location: Italy

Description

This is a thematic module showcasing applications of Data Science and AI tools to different fields e.g. drug design and drug discovery, physiological/physical analysis of athletes to improve performance, risk analysis in the insurance business, finance, and energy distribution optimization. The course will allow you to put into practice the knowledge, tools, and methodologies learned in the previous modules, by applying the to real-life applicative scenarios.

Applied Artificial Intelligence

Professors

Pierluigi Casale
Pierluigi Casale
PhD @ Universitat de Barcelona, Former Innovation Officer (Data Science and AI) @ European Parliament, Principal Data Scientist @TomTom. Location: Italy

Description

An applied Artificial Intelligence course focuses on teaching students how to use and apply various artificial intelligence (AI) techniques and technologies to solve real-world problems. Topics include: Data preprocessing and cleaning, Building and training AI models (using popular software frameworks and tools such as TensorFlow, PyTorch, and scikit-learn), and Deploying AI models in real-world applications, including ethical considerations, security concerns, and privacy issues. Overall, the goal of the course is to equip students with the skills and knowledge they need to build and apply AI models to solve real-world problems in various industries and domains.

Applied Machine Learning

Professors

Sabya Dasgupta
Sabya Dasgupta
Lead Solution Architect @ Microsoft, Big Data & MLOps technologist. Location: Canada

Description

The course introduces students to the principles and techniques of machine learning and their practical applications. The course covers topics such as data preprocessing, feature engineering, model selection, and evaluation. Students will learn how to implement algorithms for supervised and unsupervised learning, and how to interpret and visualize the results. They will also gain hands-on experience with popular machine learning tools and libraries such as scikit-learn and TensorFlow. The course will equip students with the knowledge and skills necessary to develop and apply machine learning solutions in real-world scenarios.

Behavioral Cybersecurity [Elective]

Professors

Tom Vazdar
Tom Vazdar
Chief Security Officer @ Erste Bank Croatia, Advisory Board Member at EC3 European Cybercrime Centre @ Europol

Description

Exploring the human side of cybersecurity, this course addresses behavioral patterns contributing to vulnerabilities. It focuses on understanding psychology, cultivating a security-conscious culture, and mitigating human-related risks.

Big Data and Cloud Computing Infrastructure

Professors

Lokesh Vij
Lokesh Vij
Software Engineer @ Symantec, Part-Time Faculty @ Seneca College. Location: Canada

Description

The course is designed to give students a non-excessively technical introduction to the architectures, technologies, and tools used to manage and analyze large datasets in cloud computing environments. Topics covered may include Hadoop, Spark, NoSQL databases, data warehousing, and cloud infrastructure such as AWS, Azure, and Google Cloud.

Blockchain for Business [Elective]

Professors

Description

This course provides a comprehensive exploration of blockchain technology and its transformative impact on business practices. Covering fundamental concepts, decentralized nature, and reshaping processes, participants delve into various blockchain types and consensus algorithms. The curriculum explores smart contracts, Decentralized Applications (DApps), real-world use cases, security measures, legal implications, and enterprise-grade platforms. Discussions include integration strategies, governance models, scalability challenges, and solutions for broader adoption in business contexts.

Business Communication

Professors

Paco Awissi
Paco Awissi
Vice President of Data and Reporting @ Morgan Stanley, Lead Instructor @ McGill University School of Continuing Studies. Location: Canada

Description

The course various aspects of communication in a business context, such as effective writing, public speaking, interpersonal communication, and the use of digital media. Students will learn strategies for creating and delivering presentations, writing reports and proposals, and communicating with stakeholders within and outside of an organization.

Business Fundamentals

Professors

Description

In this course, students will delve into essential business dynamics, from corporate strategy to market management. Explore financial basics, growth strategies, and market analysis techniques. Differentiate between business and consumer markets, grasping core marketing principles. Gain insights into the business world's overview, sectors, and societal impact. Embrace digital business through a concise study of branding and the marketing mix.

Business Intelligence and Decision Making [Elective]

Professors

Description

The course highlights the pivotal role of Business Intelligence (BI) in data-driven decision-making within organizations. Emphasizing strategies for data curation, integration, and analysis, the curriculum explores data warehouse architecture, storage solutions, and effective BI implementation. Topics encompass visualization techniques, KPI implementation for performance monitoring, and leveraging data insights through scenario analysis. Students also familiarize themselves with popular BI tools and real-world applications, addressing ethical considerations in data handling.

Business Problem Solving

Professors

Santhosh Suresh
Santhosh Suresh
Head of Product Data Science @ PayPal, formerly @ Meta and McKinsey, PhD @ University of Michigan Ross School of Business. Location: California

Description

This course covers various problem-solving methods and tools to help students analyze and address complex business issues. Specific topics covered include techniques for decision-making and creative problem-solving. The course also explores different types of business problems, such as financial, operational, marketing, and strategic issues. Students are introduced to case studies and simulations that require them to apply problem-solving skills to real-world business situations. The goal of the course is to equip students with the skills and strategies needed to identify, analyze, and solve problems in a business context.

Business Resilience and Response Strategies

Professors

Dimitris Tolis
Dimitris Tolis
Deputy Chief Information Security Officer @ European Investment Bank (EIB), Certified CISSP and CCNA. Location: Luxembourg

Description

This course highlights business resilience against cybersecurity threats, covering continuity strategies, disaster recovery, and effective responses to breaches for risk mitigation and ensuring seamless operations.

Business Strategy

Professors

Francesco Derchi
Francesco Derchi
Adjunct Faculty @ École Hôtelière de Lausanne, Course Director @ Harvard Business Review, Advisory Board Member @ Arsène Lippens. Location: Switzerland

Description

The Business Strategy module is designed to provide students with a comprehensive understanding of the critical concepts and frameworks for developing effective business strategies in the digital age. Students will learn how to assess the competitive environment and develop a competitive strategy to gain a competitive advantage. They will also learn the importance of developing a digital business model and implementing a digital marketing plan to drive customer acquisition and retention. By the end of the course, students will be equipped with the skills and knowledge necessary to develop and implement effective business strategies in the digital world.

Capstone Project and Dissertation

Professors

Description

The Capstone Project and Dissertation, also known as the MSc thesis, is the pivotal project in the MSc program, aimed at consolidating acquired skills through a research endeavor. Collaborating with an OPIT supervisor, each student develops a project proposal realized in the final terms of their MSc program. The project entails research of industrial relevance, exploring methodological and/or practical aspects within program domains and beyond. Depending on the chosen exit point (30 or 60 ECTS), the MSc thesis workload is distributed over 1 or 2 terms, respectively. Students also have the opportunity to integrate internships with industrial partners to complement and complete their MSc thesis.
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