My AI DevCamp Journey
I’m someone who loves to plan. I always make 1-year, 3-year, and 5-year plans. Sometimes, not everything goes according to plan, unexpected things can happen along the way but planning is always good for a successful career.
Last December, while planning for 2024, I was deeply immersed in a journey I had eagerly followed. I had taken various courses to develop myself in this field, and my goal was to apply AI technology to my web and mobile projects.
In April, I saw a post on LinkedIn from GDG London. They were organising an 8-week AI DevCamp. This was a great opportunity because receiving training from such valuable mentors would help me grow and be a significant step for my career. Additionally, as I gain more experience, I can incorporate AI technology into my projects.
The first course started on May 16th. Every week, on Thursdays and Saturdays, I received training from highly esteemed mentors. I learned new information each week and gradually delved deeper into the world of AI. Then I received my certificate with a wonderful ceremony.
Throughout this journey, I documented my learnings and insights in weekly articles. Let's review what topics we covered together:
- Journey into the World of Artificial Intelligence (Week 1): In the first week, we provided a comprehensive introduction to the field of Artificial Intelligence (AI). Fundamental concepts defining AI were explained, including the distinctions between AI, machine learning, and deep learning.
- Responsible AI (Week 2): In the second week, we focused on Responsible AI, a critical area that addresses the ethical implications of developing and deploying AI technologies. This week emphasised ensuring that AI systems are fair, transparent, and unbiased.
- Deep Learning (Week 3): In the third week, we focused on deep learning, a subset of machine learning that has driven many of the most significant advancements in AI in recent years. This week covered the fundamentals of neural networks, different neural network architectures, and the challenges of training deep learning models.
- Natural Language Processing (Week 4): In the fourth week, we focused on Natural Language Processing (NLP), which enables machines to understand, interpret, and generate human language.
- Generative AI (Week 5): In the fifth week, we were dedicated to Generative AI, which involves creating AI models that can produce new content, such as images, text, music, and even video. This week explored how generative models like GANs and VAEs work and their ability to generate realistic content.
- Advanced Generative AI Techniques (Week 6): In the sixth week, we focused on advanced techniques in Generative AI that pushed the boundaries of what AI can create. Additionally, ethical considerations regarding the training and use of such models were addressed.
- ML Engineering: From Modeling to Production (Week 7–8): In the final two weeks we were dedicated to Machine Learning Engineering, focusing on the processes and best practices for taking AI models from the research and development stage to production. This part of the Al DevCamp emphasized the importance of scalability, reliability, and efficiency in deploying AI models in real-world environments.
I've always found joy in sharing the knowledge I've gained with others. Each week, I wrote and shared these blog posts on LinkedIn, X and in our community’s Slack channel to benefit others.
You can find all the notes from my 8-week journey on my blog.
I believe that learning to improve oneself, sharing what you've learned with others, and gaining experience together are all invaluable.
Enjoy reading!