Bachelor of Science (BSc) in Computer Science and Digital Technology
Welcome to a launchpad for the next generation of tech pioneers at our Paris Bagnolet campus. Situated in the heart of one of Europe’s most iconic tech hubs, this programme is where creative problem-solving meets deep technical expertise. This isn’t just a computer science degree; it’s a toolkit for the digital architect. In a world where code runs our lives and data is the new currency, we go beyond syntax and logic. We bridge the gap between abstract algorithms and the tangible impact of technology on society and business. Whether your goal is to architect the next viral app, defend global infrastructure against cyber threats, or build AI that changes how we live, our curriculum gives you the technical muscle and entrepreneurial mindset to make it happen.
At EIIET, we know that the tech world moves fast. We don’t just teach you how to use current tools; we teach you how to build the ones that don’t exist yet. Our hands-on approach ensures that you aren't just sitting behind a screen—you’re collaborating, innovating, and preparing to lead in a global economy that is digital-first.
| Type of Study: |
Bachelor of Science (BSc) |
| Major: | Software Engineering & Digital Innovation |
| Field of Study: |
Computer Science & Information Technology |
| Speciality Subjects: |
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| Campus Location: |
Bagnolet, France |
| Study Mode: |
Full-time (on campus) |
| Duration: | 3 years (6 Semesters) |
Offered Specialty Courses
- Artificial Intelligence (AI)
- Machine Learning & Data Mining
- Cyber Security & Data Protection
- Data Structures and Algorithms
- Software Development Practices
This module takes you from the basic logic of algorithms to the frontiers of cognitive computing, focusing on the transformative power of intelligent systems. In an era where data is the most valuable resource on earth, Artificial Intelligence is the engine that turns that raw information into foresight, automation, and innovation. You will learn to move beyond being a consumer of tech to becoming an architect of the future, understanding that the most powerful AI isn't just about "cool code," but about solving human problems at scale.
You will learn to master the "intelligence transition." From designing neural networks that can recognize patterns invisible to the human eye to deploying ethical AI frameworks that ensure fairness and transparency, this subject ensures you can lead the digital charge with responsibility and technical depth. In a landscape where technology evolves by the hour, you will become the specialist who doesn't just follow trends, but builds the autonomous systems and predictive models that define the new standard of global industry.
- Foundations of Machine Learning: Dive into the core of how machines "learn." Master supervised, unsupervised, and reinforcement learning techniques to create systems that improve themselves through experience.
- Neural Networks & Deep Learning: Explore the architecture of the digital brain. Learn to build multi-layered models that power everything from voice recognition and computer vision to advanced medical diagnostics.
- Natural Language Processing (NLP): Bridge the gap between human speech and machine understanding. Learn the mechanics behind chatbots, real-time translation, and sentiment analysis tools that interpret the nuances of language.
- AI Ethics & Governance: Tackle the most important question in tech: "Just because we can, should we?" Develop the frameworks to identify bias, ensure data privacy, and lead the ethical deployment of AI in a way that benefits society.
- Deployment & Scaling: Move your models from the local lab to the global cloud. Learn to integrate AI into existing software ecosystems, ensuring your solutions are robust, secure, and ready for real-world traffic.
Career Opportunities
Expertise in Artificial Intelligence positions you as a "Visionary Architect." As industries from finance to healthcare race to automate and optimize, the demand for professionals who can bridge the gap between complex mathematics and practical application is skyrocketing.
- AI Developer / Engineer: Designing and implementing the complex algorithms and software that power autonomous systems and intelligent applications.
- Machine Learning Specialist: Focusing on the data-driven models that allow computers to predict market trends, customer behavior, and operational needs without explicit programming.
- Data Scientist: Uncovering the "hidden gold" in massive datasets, using AI tools to provide the strategic insights that drive executive decision-making.
- AI Product Manager: Leading cross-functional teams to bring AI-powered products to market, ensuring technical feasibility meets commercial demand.
- Computer Vision Researcher: Developing the technology that allows machines to "see" and interpret the physical world, essential for robotics and self-driving vehicles.
- Ethics & Compliance Officer (AI): Ensuring that an organization’s automated systems are transparent, unbiased, and compliant with emerging global regulations.
- Automation Consultant: Helping legacy businesses transform their manual workflows into streamlined, AI-enhanced operations to stay competitive.
- Chief Technology Officer (CTO) Path: Positioning yourself for the boardroom by mastering the most disruptive technology of the 21st century and defining a company’s long-term digital roadmap.
This module takes you deep into the engine room of the modern world, where raw data is refined into strategic intelligence. In a digital landscape overflowing with information, the ability to find "the needle in the haystack" is a superpower. You will learn that Data Mining isn't just about collecting numbers—it’s about discovering the hidden relationships, trends, and anomalies that others miss. We move you beyond static spreadsheets to show you how to build dynamic systems that uncover the "why" behind the "what."
You will learn to master the "predictive edge." From identifying subtle shifts in consumer behavior before they happen to detecting fraudulent transactions in milliseconds, this subject equips you with the tools to turn historical data into a crystal ball for business. In a world where companies are drowning in data but starving for insights, you will become the expert who builds the pipelines and models that transform "big data" into big impact, ensuring organizations don't just react to the market, but stay three steps ahead of it.
- Pattern Discovery & Pattern Recognition: Master the art of spotting the invisible. Learn to use clustering and association rules to group complex data points and identify recurring sequences in massive datasets.
- Supervised & Unsupervised Learning: Gain hands-on experience with the dual pillars of ML. Build classification models to predict specific outcomes and use dimensionality reduction to simplify high-dimensional data without losing its essence.
- Data Pre-processing & Feature Engineering: Learn the "dirty work" that makes high-performance AI possible. Master the techniques for cleaning noisy data, handling missing values, and selecting the most impactful variables for your models.
- Predictive Modeling & Forecasting: Move from analysis to anticipation. Use regression analysis and time-series forecasting to predict everything from stock market fluctuations to energy consumption demands.
- Big Data Architectures: Understand the scale of modern computing. Learn how to apply mining and learning techniques within distributed environments like Hadoop and Spark, ensuring your solutions can handle petabytes of information.
Career Opportunities
Expertise in Machine Learning & Data Mining turns you into a "Strategic Architect of Information." As every sector—from retail to aerospace—becomes data-dependent, the need for professionals who can extract actionable knowledge from chaos is unprecedented.
- Machine Learning Engineer: Designing and building self-learning systems that improve over time, powering recommendation engines and predictive maintenance tools.
- Data Scientist: Serving as the bridge between data and the boardroom, using statistical modeling to solve complex business problems.
- Business Intelligence (BI) Architect: Creating the data structures and mining processes that allow a company to visualize its performance and predict future growth.
- Quantitative Analyst (Quant): Applying data mining and ML to financial markets to develop high-frequency trading strategies and risk assessment models.
- Fraud Analyst: Building anomaly detection systems for banks and e-commerce platforms to identify and stop malicious activity in real-time.
- Customer Insights Lead: Using mining techniques to segment audiences and personalize the user experience at a massive scale.
- Bioinformatics Specialist: Applying data mining to genomic sequences and biological data to accelerate drug discovery and personalized medicine.
- Chief Data Officer (CDO) Path: Positioning yourself for the executive suite by overseeing an organization’s entire data lifecycle and turning information into a primary competitive advantage.
This module takes you from the basics of digital hygiene to the sophisticated defense of global networks. In an age where data is more valuable than gold—and twice as targeted—Cyber Security is the vital shield that keeps our digital world turning. You will learn to move beyond being a passive user of technology to becoming its guardian, understanding that true security is not just about building taller walls, but about outsmarting the adversaries who seek to climb them.
You will learn to master the "defense-in-depth" mindset. From deciphering the complex mathematics of modern cryptography to navigating the high-stakes legal landscape of the GDPR, this subject ensures you can protect personal privacy and corporate integrity with equal skill. In a world where a single breach can topple a multinational or compromise national security, you will become the expert who doesn't just respond to threats, but anticipates them—building resilient, bulletproof systems that safeguard our collective future.
- Network Defense & Infrastructure Security: Master the art of the perimeter. Learn to configure intelligent firewalls, intrusion detection systems (IDS), and secure protocols to keep unauthorized eyes off sensitive data traffic.
- Ethical Hacking & Penetration Testing: Think like the adversary to beat the adversary. Gain hands-on experience in "white-hat" hacking, identifying vulnerabilities in code and systems before malicious actors can exploit them.
- Applied Cryptography: Uncover the science of secrets. Study the algorithms that power end-to-end encryption, digital signatures, and secure authentication, ensuring that data remains unreadable even if it falls into the wrong hands.
- Data Protection Law & Digital Ethics: Navigate the legal maze. Deep dive into the GDPR and global privacy frameworks to understand the rights of individuals and the heavy responsibilities of those who manage their information.
- Incident Response & Digital Forensics: Learn what to do when the alarms go off. Develop the skills to contain a breach, recover lost data, and perform forensic investigations to trace an attack back to its source.
Career Opportunities
Expertise in Cyber Security & Data Protection positions you as a "Guardian of the Digital Frontier." As cybercrime continues to evolve into a multi-trillion dollar industry, the demand for specialists who can outpace threat actors is at an all-time high across every sector.
- Cyber Security Analyst: The first line of defense, monitoring networks for suspicious activity and implementing the immediate protocols that stop an attack in its tracks.
- Ethical Hacker / Penetration Tester: Working as a professional security auditor to "stress-test" company defenses and find the gaps that need fixing.
- Information Security Manager (CISO Path): Designing the overarching security strategy for an entire organization, balancing technical needs with business goals and budget.
- Data Privacy Officer (DPO): Ensuring that a company’s use of personal information is fully compliant with international laws, acting as the bridge between legal and tech departments.
- Digital Forensics Investigator: Working with law enforcement or private firms to uncover evidence after a cybercrime, analyzing hardware and traffic to build a case.
- Security Software Developer: Building the very tools that provide protection, from advanced antivirus engines to secure communication platforms.
- Cloud Security Specialist: Protecting data and applications as they migrate to the cloud, ensuring that decentralized systems remain as secure as private servers.
- Risk & Compliance Consultant: Advising businesses on how to minimize their "attack surface" and meet the strict security standards required by modern industry regulations.
This module takes you under the hood of modern software, where efficiency is the difference between a seamless user experience and a system crash. In the world of high-performance computing, it’s not just about writing code that works—it’s about writing code that scales. You will learn to move beyond basic scripting to master the "logic of efficiency," understanding that the way data is organized and manipulated is the heartbeat of every powerful application, from Google’s search engine to the high-frequency trading platforms of Wall Street.
You will learn to master the "complexity trade-off." From choosing the perfect data container for a massive social media feed to optimizing the search paths that power GPS navigation, this subject ensures you can solve problems with mathematical precision. In an industry where "Big O" notation is the language of professional excellence, you will become the engineer who doesn't just build features, but crafts elegant, lightning-fast solutions that minimize memory usage and maximize speed, even when dealing with billions of data points.
- Fundamental Data Structures: Master the building blocks of memory. Deep dive into arrays, linked lists, stacks, and queues to understand how to store and access information with surgical precision.
- Sorting & Searching Algorithms: Learn the "mechanics of order." Explore everything from classic QuickSort and MergeSort to the sophisticated binary search algorithms that allow computers to find a single entry in a mountain of data in milliseconds.
- Trees & Graphs: Map the connections of the digital world. Understand how hierarchical structures and network graphs power everything from organizational charts to the complex routing of the internet and social networks.
- Algorithm Analysis (Big O): Develop a critical eye for performance. Learn to analyze the time and space complexity of your code, ensuring your solutions remain robust as the workload grows from ten users to ten million.
- Dynamic Programming & Recursion: Solve the "impossible" by breaking it down. Master the advanced problem-solving techniques used to tackle complex, overlapping sub-problems, turning exhaustive computations into streamlined, efficient processes.
Career Opportunities
Expertise in Data Structures & Algorithms positions you as a "Master of Optimization." This is the core knowledge tested by top-tier tech firms (like Google, Amazon, and Meta) because it proves you have the analytical depth to handle their most difficult technical challenges.
- Software Engineer (Backend): Designing the core logic and server-side processes of applications where speed and data integrity are the highest priorities.
- Algorithm Engineer: Specializing in the development and fine-tuning of the complex mathematical procedures that drive specialized software like autonomous driving or image processing.
- Systems Architect: Planning the high-level structure of complex software systems, ensuring that data flows efficiently between different components.
- Game Developer: Optimizing the real-time physics and rendering engines of video games, where every millisecond of algorithmic efficiency counts toward a smooth experience.
- Competitive Programmer / Tech Interview Coach: Using your deep knowledge of problem-solving to excel in high-stakes coding environments or help others break into the world's leading tech companies.
- Database Developer: Designing the underlying structures that allow databases to store, retrieve, and index information at massive scales without slowing down.
- Quantitative Developer: Implementing the lightning-fast algorithms used in finance to execute trades and analyze market risk in fractions of a second.
- Research Scientist (CS): Pushing the boundaries of what computers can do by discovering new, more efficient ways to process information and solve the world's most complex computational puzzles.
This module takes you from writing simple scripts to engineering professional-grade software that stands the test of time. In the high-velocity world of tech, "it works on my machine" is never enough. Software Development Practices is the discipline of creating code that is clean, scalable, and collaborative. You will learn to move beyond being a solo coder to becoming a vital part of a high-performing engineering team, understanding that great software is as much about human communication and systematic process as it is about syntax.
You will learn to master the "quality lifecycle." From the initial spark of a user requirement to the automated pipelines that deploy updates to millions, this subject ensures you can navigate the modern developer’s toolkit with ease. In an industry where technical debt can sink a startup, you will become the engineer who builds for the long term—mastering the art of testing, the rigor of version control, and the agility of modern methodologies. You won't just write code; you will craft software that is resilient, maintainable, and ready for the real world.
- The Software Development Life Cycle (SDLC): Master the roadmap of creation. Learn to navigate various models—from the structured discipline of Waterfall to the rapid, iterative pulse of Agile and Scrum—ensuring you choose the right process for the project’s goal.
- Version Control & Collaboration (Git): Own your history. Learn to use Git and GitHub to manage codebases, handle complex merges, and collaborate across global teams without ever losing a line of work.
- Clean Code & Design Patterns: Write for humans, not just machines. Master the "SOLID" principles and common design patterns to ensure your code is readable, reusable, and easy for the next developer to understand.
- Automated Testing & Quality Assurance: Build your own safety net. Learn to write unit tests, integration tests, and end-to-end suites that catch bugs before they reach the user, ensuring "Day 1" quality every day.
- CI/CD & DevOps Foundations: Bridge the gap between code and cloud. Explore Continuous Integration and Continuous Deployment (CI/CD) pipelines that automate the build and release process, making deployment a non-event.
Career Opportunities
Expertise in Software Development Practices positions you as a "High-Value Engineer." Companies don't just want coders; they want professionals who understand how to deliver reliable products in a professional ecosystem.
- Full-Stack Software Engineer: Designing and maintaining both the user-facing and server-side components of applications using professional industry standards.
- DevOps Engineer: Specializing in the automation of software delivery, ensuring that code moves from a developer's laptop to production as quickly and safely as possible.
- Quality Assurance (QA) Automation Engineer: Building the sophisticated testing frameworks that ensure complex software systems remain bug-free as they grow.
- Technical Lead: Guiding engineering teams through the architectural and process decisions that define a project’s success and long-term health.
- Build & Release Manager: Overseeing the complex coordination required to ship large-scale software updates across global platforms.
- Software Architect: Mapping out the high-level structures and practices that multiple teams will follow to build a unified, scalable digital ecosystem.
- Systems Integration Specialist: Ensuring that different software systems communicate effectively and reliably, following strict architectural best practices.
- Chief Technology Officer (CTO) Path: Positioning yourself for leadership by mastering the "how" of software creation—building the teams and processes that allow an organization to innovate at scale.
Eligibility Requirements
Academic Qualifications: A certificate of your higher secondary education.
English Language requirements
- Recognized English tests:
1.1 IELTS — Overall 6.0
1.2 TOEFL:
1.2.1 PBT (Paper-Based Test) — 550 points
1.2.2 CBT (Computer-Based Test) — 213 points
1.2.3 iBT (Internet-Based Test) — 79–93 points - Nationals from English-speaking countries can skip taking an English test. They should write a letter of motivation for themselves.
- A minimum of 50% of grades in English subjects at higher secondary education or the medium of studies should be English in the last school of education.
Intakes
January/April/July/October
Course Fee
International student fee: €9,899/year | EU student fee: €7,999/year.
Admissions are open for the 2026 intake
You can start applying for a Bachelor of Science in Computer Science and Digital Technology now.
Programme Advisor
Contact: +33759339441
Email: admission@eiiet.com