Strong foundations: Master math, statistics and programming languages such as Python.

Machine Learning: Gain expertise in ML algorithms, supervised and unsupervised learning, and frameworks such as TensorFlow and PyTorch.

Data Processing: Develop skills in data collection, pre-processing and analysis using tools such as Pandas and SQL.

Deep Learning: Dive into neural networks, CNNs, RNNs and other advanced deep learning techniques.

Real-world projects: Build a portfolio of diverse projects showcasing your AI solutions to real-world problems.

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