Python and Pandas for Data Engineering

• Techniques for Word Feature Conversion: Gain knowledge of methodologies such as one-hot encoding, bag-of-words, embeddings, and embedding bags for the transformation of words into features.

• Contextual Embedding Utilizing Word2Vec: Acquire practical expertise in the application of Word2Vec models for the generation of contextual embeddings.

• Constructing a Fundamental Neural Network Language Model: Comprehend the methodology for constructing a fundamental language model utilizing a neural network.

• Applying N-Gram and Sequence-to-Sequence Models: Investigate N-gram models and sequence-to-sequence architectures for applications including document classification, text analysis, and sequence transformation.

Level: Beginner

Certification Degree: yes

Languages the Course is Available: 1

Offered by: On edX provided by AI

Duration: 3�6 hours per week 4 weeks (approximately)

Schedule: Flexible