This course introduces learners to the powerful world of Machine Learning for Time Series Forecasting. Focusing on using Python and popular libraries such as Scikit-learn and TensorFlow, learners will explore techniques to predict time-based data like financial market trends, temperature, and more. The course covers theoretical foundations as well as practical applications, making it ideal for those looking to enter the field of AI or data science.

The course stands out by providing hands-on experience through real datasets, such as stock prices, and teaching learners how to analyze and improve their models using techniques like Neural Networks and Long Short-Term Memory (LSTM). At the end of the course, learners will have the skills to build and evaluate accurate time series forecasting models for real-world data analysis.