Good evening today I started learning about AI, I have learned what AI is , what it can and can’t do , I have learned its uses for ML and DS , as well as DL. I want to continue to learn and evolve it. Can you give me a Roadmap to learn and evolve on it?
3 Likes
So, it is a good time to start the MLS from Prof. Ng. That will leverage your understanding into practical usages. After you finished that specialization, better to start DLS next. Later, you will find out by yourself what you want to learn.
Also make sure to check out the mathematical specialization from DeepLearning.AI if you are not sure about your math level.
4 Likes
If I don’t know a programming language can I get a job after a lot of training on AI , or do I have to learn one , and if so which one is better ?
1 Like
My plan is →
- Python oops
- Python Data structures
- SQL
- Mathematics for machine learning
- Pandas,Numpy
- Matplotlib, seaborn
- EDA
- Feature engineering
- ML Specialization
- Deep-learning Specialization
- Tensorflow deployment
- Tensorflow professional certificate
- NLP specialization
- Tensorflow advanced specialization
- GAN
- Generative AI
- MLops
then choose the field you are most interested in to deep dive like nlp,CV,reinforcement learning, etc etc its endless learning
4 Likes
Thanks for the help, but what courses did you take to achieve this?
any coursera courses that you recommend?
1 Like
First thing is to enroll in an introduction to Python programming course.
After you understand the basics of Python, then I recommend you enroll in the Machine Learning Specialization.
2 Likes
I took help from various resources, like
- deeplearning.ai courses for ml,deeplearning and tensorflow related courses,
- for Python and SQL I referred YouTube and gfg,
- for EDA and feature engineering I followed Krish Nayak,
- for stats if followed Statquest and Deeplearning.ai mathematics courses.
I hope I am not breaking any community guidelines by talking about external sources. If I do please let me know.
2 Likes