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Introduction to AI and Machine Learning
Explore the future of technology! In this two-week intensive course, participants will dive into the fascinating world of Artificial Intelligence (AI) and Machine Learning (ML) with a special focus on Large Language Models (LLMs).
Teaching period:
-
Application period:
31.1.2025 – 31.5.2025
Course format:
Campus
Duration:
2 weeks
part-time
Course level:
Undergraduate
Field of study:
Technology and Engineering
Credits:
3 ECTS
Organiser:
Aalto University
Tuition fees:
1170€
This summer course, tailored for beginners from diverse fields, simplifies the complexities of artificial intelligence (AI) and machine learning (ML) through engaging, hands-on experiences and real-world applications. With a special focus on Natural Language Processing, you will gain practical skills and insights to navigate the world of AI on a deeper level.
You will explore the fundamental principles of AI and ML, learn about data preprocessing techniques, and understand the architecture and functionality of large language models (LLMs) like BERT and GPT. During the course, you will also engage in practical activities, such as building sentiment analysis models, fine-tuning pre-trained LLMs, and deploying them in various applications, including chatbots and text generation tools.
The course will also cover the ethical considerations and challenges associated with LLMs, providing a comprehensive understanding of these powerful models' potential and limitations.
This workshop-based summer course is ideal if you are looking to gain practical knowledge and experience in AI and ML, with a particular emphasis on the transformative capabilities of large language models. By the end of the course, you will have a strong foundation in AI and machine learning. You will also be equipped with the skills to apply large language models to solve real-world challenges and develop innovative solutions within your respective fields.
21 July-1 August 2025: Lectures and workshops on-site at Aalto University campus
- Daily lectures and workshops (Monday-Friday) between 09-12
- Independent study time and group project work
- Optional social program in the evenings
| WEEK 1 | Monday 21 July | Tuesday 22 July | Wednesday 23 July | Thursday 24 July | Friday 25 July |
|---|---|---|---|---|---|
| Morning (9-12) | Introduction to AI, ML, and LLMs |
Basics of Machine Learning |
Data Preprocessing for NLP |
Introduction to LLMs and Their Applications |
Supervised Learning for NLP Tasks |
| Afternoon (13-16) |
Individual or group work | Individual or group work | Individual or group work | Individual or group work | Individual or group work |
| WEEK 2 | Monday 28 July | Tuesday 29 July | Wednesday 30 July | Thursday 31 July | Friday 1 August |
|---|---|---|---|---|---|
| Morning (9-12) |
Advanced NLP Techniques |
Language Generation with LLMs |
Ethical Considerations and Challenges in LLMs |
Model Deployment and Integration in Applications |
Final Project and Presentation |
| Afternoon (13-16) |
Individual or group work | Individual or group work | Individual or group work | Individual or group work |
*Note that this is a preliminary schedule subject to change or updates.
Understand core concepts
- Learn the fundamentals of AI and ML with a focus on large language models (LLMs).
- Explore the architecture and functionality of models like BERT and GPT.
Preprocess text data
- Perform tokenisation, stemming, lemmatisation, stop-word removal, and vectorisation.
- Use tools like NLTK and SpaCy to clean and prepare text data.
Apply machine learning to NLP and develop NLP applications
- Implement supervised learning for tasks like sentiment analysis and text classification.
- Fine-tune pre-trained LLMs using frameworks like Hugging Face’s Transformers.
- Build and deploy language generation tools such as chatbots and text generators.
Analyse and mitigate ethical concerns
- Identify ethical challenges like bias and data privacy in LLMs.
- Develop strategies to reduce bias and promote responsible AI use.
Deploy and integrate models
- Deploy AI/ML models on cloud services and edge devices.
- Implement end-to-end solutions showcasing LLMs in practical applications.
Engage in hands-on projects
- Collaborate on a real-world NLP project using LLMs.
- Present project outcomes, demonstrating real-world impact and innovation.
The working and teaching methods are interactive and engaging, combining various instructional strategies.
- The course fosters an active learning environment by combining lectures, hands-on practical sessions, and collaborative group activities.
- Lectures introduce theoretical concepts and industry applications, while practical sessions allow participants to work directly with tools and frameworks used in AI and ML.
- Group discussions and peer-to-peer learning encourage participants to share insights and collaborate on problem-solving, enhancing their understanding and application of Large Language Models in real-world scenarios.
- Additionally, the use of online resources and guided self-study support independent learning and reinforce key concepts outside of the classroom.
Course workload
Lectures and practical sessions 30h
Independent study 21h
Project work and assignments 30h
Total workload 81h (3 ECTS)
The course is graded as pass/fail.
Please note that the undergraduate courses offered by Aalto University Summer School can not be included in Aalto degree studies.
The course does not require any specific prerequisites. It is ideal for individuals from diverse backgrounds, including students, professionals, and enthusiasts looking to enhance their understanding of artificial intelligence and machine learning, particularly in the context of Large Language Models. Those in fields such as engineering, data science, software development, and business will benefit from the practical skills gained in applying AI techniques to solve real-world problems. The workshop also equips participants with tools to navigate the rapidly evolving AI landscape.
Participants must have completed a high school or vocational degree or equivalent by the time the course starts. However, they do not have to be a degree student at a university to participate in our courses.
Additionally, all summer school course students must be 18 years or older, as it is the legal age in Finland.
Please include a motivation letter or video in your application. In your motivation letter or video, describe your motivation for taking this course. The recommended length for the motivation letter is 150-250 words, and 1-2 minutes for the video.
Tuition fees for Summer School courses
One course: 1170€ (incl. VAT 25,5%)
- The course fee includes academic course sessions and assignments, an official digital Aalto University certificate and support from the Summer School team. The fee does not cover accommodation, daily meals, or transportation during the course
- Unfortunately, Aalto University Summer School does not offer scholarships for participants.
Social program fee
If you need a visa, we recommend applying by April 15th 2025.
- This is to ensure that we have enough time to process your application and that you have time to make the tuition fee payment, book a visa appointment and wait for the application to be processed.
- You can apply and be accepted to the courses after April 15th. In that case, we recommend that you pay at your earliest convenience so that we can deliver your invitation letter to you promptly.
- According to the Ministry of Foreign Affairs of Finland, the processing time for a visa application is 15 days. However, the processing time may be longer if a more detailed application examination is required.
Learn about the Aalto University Summer School cancellation terms. You will receive the full terms before making the payment and confirming the course participation.
Teacher Information
Doctor of Science (SDr.) Dariush Salami is a distinguished Radio Research Scientist at Nokia Bell Labs. He has deep expertise in AI and machine learning for wireless networks, including cutting-edge 5G and 6G technologies. He earned his PhD from Aalto University as a Marie Skłodowska Curie fellow, focusing on human-centric sensing using mmWave radars.
Salami has extensive industrial experience, notably serving as the CTO of Rectified.ai, a platform-agnostic automatic machine-learning solution. He has lectured the Machine Learning D course for nearly 1000 students, making it the largest AI/ML course in Finland.
His innovative work is recognised through several patents and numerous publications in prestigious journals. Additionally, he has secured multiple grants, including from the Nokia Foundation and Google, underscoring his contributions to advancing technology.
Summer School Team
Aalto University Summer School
Make this summer unforgettable and experience the best of Aalto University and Finland under the Nordic summer sun.
Information for Summer School Applicants
Get to know the application guidelines and tuition fees.
Travel arrangements for Summer and Winter School students
Learn about the guidelines for visa application and budgeting for your stay during the summer course.
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