Full MOOCs
If you really want to achieve some progress you need to spend more time and learn more than by listening to some introductions. I've collected some MOOCs that run over multiple weeks. Some of them are free, as long as you don't need a certificate. Others cost some bucks, but this investment is definitely worth it - as long as you really complete the course
Deep Learning specialization
by Andrew Ng + 2
https://www.coursera.org/specializations/deep-learning
This MOOC is probably the most famous. It is being taught by Andrew Ng who is founder of deeplearning.ai and Co-Founder of coursera. The specialization consists of 5 courses, ranging from general introduction to the concepts of deep neural networks to Convolutional Neural Networks (CNN, typically applied to images) and Sequence Models (best choice for langage and speech) and the implementation in TensorFlow.
Machine Learning Operations for production specialization
by Andrew Ng + 3
https://www.coursera.org/specializations/machine-learning-engineering-for-production-mlops
This MOOC is probably the most famous. It is being taught by Andrew Ng who is founder of deeplearning.ai and Co-Founder of coursera. The specialization consists of 5 courses, ranging from general introduction to the concepts of deep neural networks to Convolutional Neural Networks (CNN, typically applied to images) and Sequence Models (best choice for langage and speech) and the implementation in TensorFlow.
Time Series Forecasting
by Toni Moses
https://www.udacity.com/course/time-series-forecasting--ud980
Forecasting is a highly relevant topic for many companies, as it can be the foundation for a reliable and efficient planning process. Yet, it brings in some peculiarities while handling time series data. In this course you will learn the basics of handling such data and how you can apply typical forecasting models to them, like Holt-Winters' method of seasonality of ARIMA models.
If after this you want to take the next step, should check out Prophet, NeuralProphet or DPDHLs fcstlib (becoming open source soon)