Throughout this course, you’ll acquire the skills to:

1. Construct and train deep neural networks, discern crucial architectural parameters, and implement vectorized neural networks for diverse applications.
2. Train and evaluate test sets, conduct variance analysis for Deep Learning applications, employ standard techniques, optimization algorithms, and construct neural networks using TensorFlow.
3. Develop Convolutional Neural Networks (CNNs) and apply them to tasks involving detection and recognition. Explore neural style transfer techniques for artistic image generation, and implement algorithms for processing image and video data.
4. Build and train Recurrent Neural Networks (RNNs), delve into Natural Language Processing (NLP) and Word Embeddings. Utilize HuggingFace tokenizers and transformer models to execute Named Entity Recognition (NER) and Question Answering tasks.

Your journey will encompass a comprehensive understanding of these concepts, providing you with a robust foundation in machine learning and deep learning applications.