Data science = Data + Domain + AI + Commonsense

Many times I read up basics again and again, Over the years, I started with Windows98 Testing, C/C++ Adapters, Nestle production support, Application support, Supply chain QA / Performance / OLTP Development, SQL Developer, BI Developer, Setting up Teams, Warranty, Refurbishment, API / Supply chain, Website A/B testing, On call support. Retail product team setup/forecasting/scaling and then a long 2-year learning curve / paid lectures / back to basics mode. More learning started after that. Getting a break needs a lot of freelance / consulting/training / applied learning. Past 3 years very focused on learning/projects/production deployments. 

Now when I teach the flow/work, there are different areas overall to understand products/domain/use cases

1. Stats, Probability A/B tests, LR
2. ML world - Decision trees, SVM, Logistic regression, Random forests
3. Some variations of it for anomaly detection, decision tree regressors, SVM regressor, loss functions, conditional random fields
4. The deep learning side of CNN, RNN, LSTM, Transformers
5. NLP side of token, embeddings, different architectures to latest state of art BERT, ChatGPT, Zero shot, few shot approaches
6. Forecast track with different models both regression/time series approaches
7. Recommendation track with basics to advanced hybrid models, user-user, item-item, hybrid, seasonal, and segment based
8. Vision side of custom object, classification, transfer learning, segmentation, applied use cases
9. World of genAI for text/vision
10. Apart from this the production/deployment architecture

Sometimes I wonder how many things we can teach someone to switch to AI / ML. Always leverage your strengths in domain/data knowledge. It is vast and increasing day by day the scope of it. To succeed it is hard to know everything but the end goal is to add value to the business / use it to fix current challenges. Balance both learning and implementation. It will be a long journey to just learn forever. 

Always blend your ideas in DATA + DOMAIN + AI + Business Value to find the right use cases.

Keep Exploring!!!