Hello! I hope you are doing well. I’ve completed MLS and DLS.
I noticed that in these courses, ready-to-use data were provided but in real life, we need to make the data ready-to-use (data cleaning, declustering, converting image/audio/video to matrix/tensor, etc.). So, what should I do next? Taking Google Data Analytics or any other course(s)?
If you are interested in learning more about the data preprocessing and other tasks related with putting a model in production, I think the next logical step would be the MLOPS course.
THIS LINK will take you to the course description. It is a step-by-step course on all that is related to a Machine Learning project, from start to finish.
When I completed MLS and DLS courses, I started participating in Kaggle competitions to get some hands-on experience with some real-life examples. As I believe that it is important to keep practicing and applying what you’ve learned through hands-on projects and exercises. This will help you develop a strong foundation in data pre-processing and data preparation, and enable you to tackle real-world problems with confidence.
Along with this, as mentioned in the above replies, you can take either the NLP or GANs specialization or the Tensorflow one.
I started with NLP as I saw that many companies need their candidates to have NLP skills. But at the end, it’s your choice.
In my field, reservoir engineering, we mostly deal with numbers and graphs. So, I am learning data science stuff. No need to take NLP/GANs.
After MLS and DLS, I am now taking MLOPS. Then plan to take TensorFlow. Is this sound good? Or need to take something else?