Master the data science lifecycle from data acquisition to model deployment.
Implement exploratory data analysis and feature engineering techniques.
Apply machine learning algorithms and understand their strengths and limitations.
Build and evaluate NLP and deep learning models.
Work with real data in a project-based environment.
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To succeed in this course, students should have the following foundational knowledge and skills:
Introductory awareness of AI/Data Science concepts (recommended but not mandatory)
Basic knowledge of any programming language (Python is preferred but not mandatory)
