For both Machine Learning and Artificial Intelligence, the main prerequisites are python, statistics, linear algebra. So, start with getting yourself familiar with these concepts before moving forward.
In Machine learning, start with learning exploratory data analysis includes univariate and bivariate analysis, handling missing values and outliers, and understanding data using visualization. After that learn supervised algorithms such as Linear regression, logistic regression, decision tree, random forest, SVD, and other ensemble techniques. Also, learn evaluation metrics to validate the performance of models.
For AI, start with understanding the TensorFlow framework and then learn in-depth about Artificial Neural Networks. After that, get familiar with deep neural networks, CNN, RNN, and Auto Encoders. I recommend checking out TensorFlow official documentation to implement basic AI applications like Image Recognition, Text Classification, Language Translation, etc.