Credentials

🔗 Certificate

Introduction

When I first heard about AI and machine learning, I figured out how to implement some basic AI codes, but I wasn’t confident about the larger scope of its applications. I thought AI was only for large-scale, high-end projects, and that you needed advanced robotics systems or powerful computers to make it work. Through these courses, I realized that AI can be implemented on even simpler systems, like Arduino, and that I could apply AI to more accessible projects.

Before taking these courses, I dabbled in AI during internships and personal projects, but Andrew Ng’s AI For Everyone and Machine Learning Specialization opened up a whole new world for me. These courses helped me realize that AI could fit into every part of my future goals. At one point, I considered focusing on cybersecurity, but these courses made it clear that AI is my true passion. Everything I want to achieve revolves around AI, and Andrew Ng’s teaching made that even clearer.

Reinforcement Learning: A Game Changer

One of the most impactful lessons was deepening my understanding of reinforcement learning. Even though I had previously used Q-learning to build a self-balancing robot, this course introduced me to more advanced concepts in reinforcement learning. For someone who has always dreamed of working with robots, this was a game changer. The idea of teaching machines to learn and adapt based on their actions was exactly what I needed for my robotics projects.

AI Beyond the Technical: Understanding the Broader Impact

Taking AI For Everyone expanded my understanding of AI beyond just the technical aspects. I realized that creating AI systems—or even founding an AI company—involves much more than just building models. It requires a strong understanding of the ethical considerations, business impact, and societal influence of AI. These are things I had never thought about before the course, and they have changed the way I think about AI.

I now understand the importance of ensuring that AI benefits everyone and doesn’t harm any segment of society. From handling biases in data to addressing ethical concerns, I’ve learned that AI has a responsibility far beyond code.

Applying What I Learned to My Projects

Since completing these courses, I’ve been working on several AI projects. One of my ongoing projects involves using Generative Adversarial Networks (GANs) to create artistic-looking dogs by blending the StyleGAN3 pretrained dog dataset with the WikiArt dataset. I’m currently fine-tuning the model to generate dog images with an artistic style, merging real-world imagery with art.

Another exciting project was building Rosie, an AI-powered robot designed to assist the elderly and disabled with daily tasks. Rosie uses advanced algorithms for autonomous navigation and object retrieval, helping users move around their homes and reducing loneliness through simple social interactions. By integrating sensors like LiDAR, IMU, and depth cameras, Rosie can navigate and interact safely in dynamic environments. These projects are just the beginning, and I’m continuing to explore more AI-driven robotics systems.

Is This Course Right for You?

For anyone looking to break into AI, especially if you already have a basic understanding of Python syntax, these courses are perfect. The Machine Learning Specialization is ideal for beginners who want to understand how AI models work, while AI For Everyone gives a broader perspective on the business and ethical implications of AI. Together, they provide a well-rounded foundation for AI.