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Dariush Salami is currently working as a Radio Research Scientist at Nokia Bell Labs and a Post-Doctoral researcher at Aalto University, specialising in AI/ML for WiFi networks, 5G, and 6G. He received his PhD from Aalto University focusing on AI/ML for Wireless Communication and Sensing. Additionally, he has given lectures at the Machine Learning D course at Aalto University, the largest AI/ML course in Finland with nearly 1000 students.

Dariush, what inspired you to design this summer course on AI and machine learning, and what do you hope students will take away from it?

The inspiration for designing this summer course on AI and machine learning comes from my passion for these transformative technologies and my desire to make them accessible to a broader audience. I believe that understanding AI and ML is crucial for navigating the technological advancements of our time and future.

My hope is that students will not only gain a solid foundation in AI and ML concepts but also develop the confidence to apply these techniques in real-world scenarios.

How does this course make complex topics like AI and machine learning accessible and engaging for students with different levels of experience?

This course is designed to be inclusive and engaging for students with varying levels of experience. We achieve this by starting with fundamental concepts and gradually building up to more complex topics in an intuitive way. Interactive lectures, real-world examples, and practical exercises are integral parts of the curriculum. We also incorporate a variety of teaching methods, including hands-on projects and group discussions, to ensure that students can relate the theoretical knowledge to practical applications. This multi-faceted approach helps explain complex topics and makes learning more engaging.

Can you share an example of a hands-on project students will work on during the course? What skills will they develop through this project?

One of the hands-on projects that students will work on involves fine-tuning a Large Language Model (LLM) for a specific task, such as sentiment analysis or text summarization. 

Through this project, students will develop skills in natural language processing, data preparation, model fine-tuning, and performance evaluation. They will also gain practical experience in using state-of-the-art AI tools and frameworks, which will be invaluable for their future endeavours in AI and ML. 

Why is now an exciting time to study AI and machine learning, and how do you see these technologies shaping the future?

Now is an incredibly exciting time to study AI and machine learning because these technologies are at the forefront of innovation across numerous industries. From healthcare and finance to transportation and entertainment, AI and ML are driving significant advancements and opening up new possibilities. As these technologies continue to evolve, they will play an increasingly critical role in solving complex problems, improving efficiencies, and enhancing our daily lives. 

The future will be shaped by AI and ML in ways we can only begin to imagine, and being knowledgeable in these fields will allow individuals to be active contributors to this technological revolution.

What advice would you give to students who are new to AI and machine learning but are eager to explore these fields?

For students new to AI and machine learning, my advice is to start with the basics and build a strong foundation. Don't be intimidated by the complexity of the field; instead, approach it with curiosity and an open mind. Take advantage of the wealth of resources available online, such as tutorials, courses, and forums. Practice is key, so work on small projects and gradually take on more challenging ones. Collaborate with peers, seek mentorship, and don't hesitate to ask questions. 

Most importantly, stay persistent and enjoy the learning journey. The field of AI and ML is vast and constantly evolving, and there are endless opportunities for those who are passionate and dedicated.