I’m currently taking some courses on Coursera, and thankfully, they’re amazing. I really enjoy learning new things and practicing with quizzes and programming assignments. I want to say thank you to everyone who put in so much hard work to make those courses possible.
My goal is to become an AI/ML engineer—someone who understands both the theory and practical aspects, with hands-on experience building fascinating applications to solve real-world problems (and yes, I hope to earn a good salary too!).
However, I’m facing a challenge. I feel like I’m taking too many courses at once. I’m consuming a lot of theory, but I haven’t created anything that I truly find useful yet. I’ve only done some programming exercises to reinforce what I’ve learned. When I want to start building something, I’m afraid I don’t know enough, and I’ll get stuck and need to learn more just to move forward. Sometimes I think that if I complete all the courses first, I’ll be able to build the perfect product—and that will make me happy. But deep down, I realize this mindset might be holding me back rather than helping.
I would truly appreciate it if anyone could share some advice or mindset that could help me change the way I approach learning.
I have also started learning AI from Great Learning, which is provided by deeplearning.ai, which is an excellent course. I am learning new things, but I also have no experience in this.
Same situation for me here. I am currently doing a lot of courses and am really ambitious to learn AI/NLP, however I haven’t done much practical stuff. It would be great to have some guide or similar fellows here maybe to work on sth together:)
I’m currently taking the Machine Learning Specialization and have previously completed “AI for Everyone,” “Building AI Voice Agents for Production,” and “Building Optimized Agentic Apps using DSPY”. While I’ve learned a lot in theory, I’m struggling to confidently apply the knowledge—especially in the labs, where I often don’t fully understand what I’m doing.
I’d love to connect with other students (or any tutor/mentor) who might be more experienced or willing to collaborate on projects. It would be great to form a group where we can support each other, build something meaningful together, and really solidify what we’re learning through practice.
If you’re interested, please reply or message me. Let’s build something great as a team!
Great! Then the recommended sequence would be MLS (Machine Learning Specialization) first, followed by DLS (Deep Learning Specialization).
Once you complete those then there are a number of ways to go depending on your interests. MLS + DLS gives you the foundation for whatever comes next.
One other point to make is that you also need some math background to understand MLS and DLS. You don’t need calculus (although it really helps with some of the intuitions), but you need to be very comfortable with at least the basics of Linear Algebra. You don’t need to know what an eigenvalue is, but you need to be very familiar with vectors and matrices and algebraic operations on them. Dot products, transposes, norms etc …
Hi Paul! I graduated in computer Engineering, so I have a foundation in calculus, linear math, equations, vectors, matrices, computational logic, algorithms, etc… Should I improve my knowledge in data analysis?
You’re good to go! With a CS degree, you already know plenty about data analysis to handle MLS and DLS. In those courses they don’t really cover how we create and curate the datasets that we need to train models: they just assume that the datasets are a given. There are some other courses about data engineering that you can take later, if your goals and interests align with that.
Let us know how it goes and the forums are here for any questions or further discussions as you proceed through the courses.
I completed Deep Learning Specialization, and I saw that they processed audio data using techniques like the Fourier Transform to create a spectrogram, I don’t really understand that. I would like to learn more about that so I can clean the data for my model. This is called Digital Signal Processing, isn’t it? Could you recommend one or more courses for me, please?