LEA.ED Applied artificial intelligence and data analysis
Why study Artificial Intelligence?
With the emergence of Industry 4.0, we envision technological revolutions that will have a profound impact on all societies on the planet. Such impacts will be felt in all areas of knowledge and creation, as well as in all human endeavors. For example, an AI application used thousands of pieces of music reflecting the themes of sports, Japanese culture, daily life, and nature to compose hundreds of options before the final version of the theme song for the Tokyo 2020 Olympic Games was chosen by Japan.
the A.C.S. inapplied artificial intelligence : machine learning and data analysis is designed to support students in acquiring key skills to design, build, analyze and optimize advanced systems using machine learning models and artificial intelligence algorithms for different types of applications and problems.
By acquiring such a certification, students will be able to perform brilliantly as AI professionals and properly address the challenges posed by Industry 4.0.
The study program A.C.S. Applied Artificial Intelligence: Machine Learning and Data Analysis aims to train computer technicians who practice their profession in the fields of artificial intelligence and data science application development in the context of Industry 4.0.
the A.C.S. inapplied artificial intelligence : machine learning and data analysis is designed to support students in acquiring key skills to design, build, analyze and optimize advanced systems using machine learning models and artificial intelligence algorithms for different types of applications and problems.
By acquiring such a certification, students will be able to perform brilliantly as AI professionals and properly address the challenges posed by Industry 4.0.
The study program A.C.S. Applied Artificial Intelligence: Machine Learning and Data Analysis aims to train computer technicians who practice their profession in the fields of artificial intelligence and data science application development in the context of Industry 4.0.
Bientôt disponible à l’automne 2024
Discover a world full of opportunities
Just like the discovery of new territories, the invention of the printing press by Gutenberg, or the invention of electricity, Internet 4.0 represents a new world full of opportunities for entrepreneurs, technicians and creators alike.
Skills
Design of artificial intelligence solutions for data exploitation
From information and data analysis to algorithm development in the appropriate programming language including debugging and visual representation of results.
Develop artificial intelligence and machine learning applications
For different target platforms and with the help of various resources, you will learn how to prepare the computer development environment, program the application logic, perform quality control and document the created application.
Use of programming languages
From the problem analysis to the solution implementation, including the use of basic algorithms, a debug and a functional test plan.
Object-oriented programming
From problem and/or requirement analysis to final implementation and documentation creation.
Use of diversified data sources
You will learn how to manage databases of different types, aggregate project-relevant data, prepare and transform them according to requirements and legislation, including for learning and testing artificial intelligence applications.
Automation of data processing tasks
From preparation to documentation to final automation, for different operating systems and contexts of use.
Session 1
Mathematics Applied to Computing I
- Master discrete mathematics, graph theory, linear algebra, and probability—key skills for designing AI models.
- Learn how matrix manipulations and optimization techniques power modern AI systems.
- Apply mathematical principles to build smarter algorithms and solve real-world challenges.
Why is this important for you?
Because these are the building blocks of AI innovation! Without these core skills, you’ll struggle to create impactful solutions. With them, you’ll unlock the potential to engineer world-changing technologies.
- Learn computing-specific French to excel in bilingual AI environments.
- Write professional emails, reports, and technical documentation with fluency.
- Gain confidence to present AI ideas to French-speaking clients and stakeholders.
How does this set you apart?
Bilingual professionals are rare and highly sought after in the AI field. This course positions you to lead projects in French-speaking markets and outshine competitors.
- Explore 39 AI job roles like Data Scientist, AI Engineer, and Machine Learning Specialist.
- Understand the skillsets required for each role and how to prepare for them.
- Build a personalized career roadmap to align your skills with the demands of the AI job market.
Why should you care about these roles?
These are the roles transforming industries. This course gives you insider knowledge to secure a place in this booming market and lead the AI revolution.
- Learn to design and implement efficient algorithms to solve real-world computational problems.
- Develop key coding skills in Python, the backbone of AI programming.
- Tackle hands-on projects to build confidence in algorithmic thinking.
How will this help you stand out?
Every top AI professional excels in algorithms. Mastering them will make you indispensable to any team working on cutting-edge AI solutions.
- Configure Python, TensorFlow, and other essential tools to build your AI development environment.
- Set up cloud platforms like AWS and Google Cloud for scalable solutions.
- Learn to preprocess and manage datasets efficiently for machine learning workflows.
Why is this your first step to success?
Because every AI journey starts here! Knowing how to set up the right tools and environments will save time and make you job-ready from day one.
Session 2
- Deepen your knowledge of graph theory, calculus, and optimization to refine AI models.
- Learn to compute derivatives and gradients for training neural networks.
- Tackle advanced mathematical problems that push AI systems to their limits.
What’s the benefit for you?
The difference between a beginner and a pro in AI is the depth of their mathematical understanding. This course ensures you’re in the pro league.
- Master technical French for AI concepts like "réseaux neuronaux" (neural networks) and "modèles prédictifs" (predictive models).
- Collaborate seamlessly with French-speaking teams on global AI projects.
- Confidently present and explain complex AI concepts in French.
Why does this matter?
Global collaboration is the future of AI. This course gives you the language skills to work with international clients and teams effortlessly.
- Learn to pitch AI-driven business ideas confidently in French.
- Develop professional language skills for networking, negotiations, and presentations.
- Bridge the gap between technical expertise and business success in bilingual settings.
How does this empower you?
In the business of AI, language can be the key to opportunity. Mastering French lets you tap into new markets and elevate your entrepreneurial potential.
- Use Python libraries like Pandas, Matplotlib, and Seaborn to clean and analyze data.
- Discover trends, patterns, and insights in datasets to solve real-world business problems.
- Build professional-grade visualizations to communicate findings effectively.
Why does EDA matter?
Data without insights is meaningless. This course teaches you how to uncover the hidden stories in data, making you an invaluable asset to any team.
- Write clean, modular Python code for scalable AI applications.
- Learn debugging, error handling, and advanced coding techniques.
- Develop hands-on skills to tackle data science and AI challenges confidently.
Why is this crucial for AI?
Python is the language of AI. By mastering it, you’re not just learning to code—you’re learning to lead.
- Master the art of explaining complex technical concepts to non-technical audiences.
- Develop skills to collaborate with diverse teams across cultural boundaries.
- Gain confidence to lead discussions and presentations in global AI environments.
How will this transform you?
AI isn’t just about technology—it’s about people. This course gives you the communication skills to connect, lead, and inspire.
Session 3
- Learn to gather data using web scraping, APIs, and survey tools like Python libraries (BeautifulSoup, Requests).
- Master relational (SQL) and non-relational (NoSQL) databases for data storage and retrieval.
- Design database schemas to optimize performance for machine learning workflows.
Why is this essential?
Because every AI model begins with data. This course ensures you know how to collect and manage it effectively, setting you up for success in real-world AI projects.
- Master R programming for cleaning, analyzing, and visualizing datasets.
- Learn to manipulate data using libraries like dplyr and tidyr.
- Create stunning visualizations with ggplot2 to communicate insights.
How does this make you stand out?
By mastering R, you gain expertise in a tool trusted by top data scientists, making you versatile and highly employable in data-focused roles.
- Learn advanced data cleaning techniques to handle missing values, duplicates, and outliers.
- Use Python libraries like Pandas and NumPy to transform, group, and reshape datasets.
- Prepare data for AI models with precision and efficiency.
Why does this matter?
Clean data is the foundation of great AI models. This course ensures your data pipelines are flawless, boosting the accuracy of your solutions.
- Master predictive modeling techniques like linear regression, logistic regression, and decision trees.
- Explore advanced algorithms like random forests and SVMs for real-world applications.
- Learn how to evaluate models using metrics like accuracy, precision, and recall.
How does this benefit you?
Supervised learning drives innovations in healthcare, finance, and beyond. This course equips you to solve high-impact problems in these industries.
- Explore the fundamentals of agents, rewards, and actions in reinforcement learning.
- Implement Q-Learning and Markov Decision Processes (MDPs) to build intelligent systems.
- Use OpenAI Gym to test and deploy reinforcement learning models.
Why is this revolutionary?
Reinforcement learning powers self-driving cars and recommendation systems. With this skill, you’re on the cutting edge of AI innovation.
- Learn to identify user needs and design innovative AI-driven solutions.
- Develop prototypes, business models, and pitches tailored to industry demands.
- Explore entrepreneurship fundamentals to bring your AI ideas to life.
How does this empower you?
AI is about solving problems. This course turns you into an innovator capable of designing solutions that people need and want.
Session 4
- Automate repetitive tasks using Python and Bash scripting to boost efficiency.
- Write scripts for file management, data processing, and system operations.
- Build end-to-end automation workflows for real-world use cases.
- Learn advanced scripting techniques, including error handling and logging.
Why is this a must-have skill?
Automation frees up time and reduces errors. This course equips you to handle repetitive tasks like a pro, allowing you to focus on high-impact AI projects.
- Discover clustering techniques like K-Means and hierarchical clustering to find hidden patterns in data.
- Master dimensionality reduction methods like PCA and t-SNE for handling high-dimensional datasets.
- Explore anomaly detection techniques for fraud prevention, cybersecurity, and quality assurance.
- Work on hands-on projects to uncover insights in unstructured data.
Why is this essential?
Unsupervised learning is key to unlocking insights in raw data. This course positions you to solve real-world problems where labeled data isn’t available.
- Gain expertise in setting up cloud environments on platforms like AWS, Azure, and Google Cloud.
- Deploy scalable AI workflows using Docker, Kubernetes, and serverless architectures.
- Manage cloud resources effectively to optimize performance and minimize costs.
- Prepare for industry-recognized certifications like the Google Cloud Associate Cloud Engineer Exam to validate your expertise.
Why does this matter?
Cloud computing is the backbone of AI scalability. This course ensures you’re not only skilled but also certified to lead in a cloud-driven industry.
- Build and train deep learning models, including CNNs for image processing and RNNs for time-series and text data.
- Learn advanced neural network architectures and optimization techniques.
- Use TensorFlow and PyTorch to implement deep learning solutions for real-world challenges.
- Solve complex problems in domains like computer vision and natural language processing (NLP).
What makes this exciting?
Deep learning powers today’s AI breakthroughs. This course equips you to design the next generation of intelligent systems.
- Learn decision-making, communication, and conflict resolution to lead AI teams effectively.
- Practice collaboration strategies for fostering innovation and team success.
- Gain experience in managing projects and presenting ideas to stakeholders.
Why is this critical?
Great AI projects need great leaders. This course gives you the tools to inspire teams and drive transformative results.
- Develop innovative AI-driven solutions using design thinking principles.
- Learn how to build prototypes, business models, and go-to-market strategies.
- Gain skills in securing funding, scaling startups, and pitching ideas effectively.
Why should you care?
AI is about solving problems, and this course empowers you to turn your ideas into impactful solutions that can disrupt industries.
Session 5
- Learn to optimize AI models for speed and accuracy using advanced techniques like quantization and pruning.
- Set up production pipelines with tools like Docker, Kubernetes, and TensorFlow Lite.
- Master monitoring and logging frameworks to ensure real-time performance of AI solutions in live environments.
- Gain hands-on experience deploying scalable, industry-ready AI solutions.
Why is this critical?
Building AI models is just the beginning—deployment is where the real value lies. This course ensures your solutions are production-ready and capable of solving real-world problems at scale.
- Use tools like Google Analytics to track user behavior and improve web performance.
- Analyze marketing databases with SQL to create segmentation strategies and actionable insights.
- Optimize marketing campaigns with data-driven recommendations and ROI analysis.
- Build skills to deliver impactful digital marketing solutions powered by data analytics.
Why is this so impactful?
Data-driven marketing drives growth in every business. This course equips you with the tools to turn raw data into actionable strategies that businesses need to thrive.
- Extract insights from textual and social network data using Python libraries like NLTK, spaCy, and NetworkX.
- Perform clustering, topic modeling, and sentiment analysis to understand user behavior and trends.
- Learn social network visualization techniques to uncover hidden relationships and insights.
- Work on real-world projects to apply data mining techniques to solve industry challenges.
Why should you care?
Social and textual data are at the heart of today’s decision-making processes. This course prepares you to unlock their full potential and solve high-impact problems.
- Build recommendation systems using collaborative filtering and content-based approaches.
- Learn to optimize search engine algorithms for better user experiences and relevance.
- Solve real-world challenges by creating intelligent systems that personalize and enhance user interactions.
- Gain hands-on experience building scalable search and recommendation engines.
What makes this exciting?
Search and recommendation systems power the biggest platforms today—from Netflix to Amazon. Learning to create these systems gives you the power to revolutionize industries.
- Apply everything you’ve learned in a real-world project or internship, solving impactful AI problems under expert mentorship.
- Exclusive Career Fairs: Every semester, we host career fairs exclusively for Unica students, connecting you with top employers actively looking for talent.
- Monthly Startup Coffee Chats: Network with startup founders during monthly coffee chats to explore industry trends, potential collaborations, and career opportunities.
- 1:1 Support for Funding Applications: Receive personalized guidance to pitch your project or startup idea to Quebec government funding programs, boosting your chances of securing financial support.
- In-House AI Lab: Be part of Unica’s upcoming in-house AI Lab, where exceptional students may be hired, and their groundbreaking ideas funded for further development.
- Gain hands-on experience while building a professional-grade portfolio to showcase your skills to future employers.
Why is this your career game-changer?
Because we don’t just teach—we invest in your future. From personalized mentorship to exclusive opportunities and funding support, Unica ensures you’re not just ready for the job market but positioned to lead and innovate.
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