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Advanced Data Science:
This Course is designed to deepen students’ expertise in machine learning, advanced AI techniques, and text mining technologies. It emphasizes practical application of theoretical concepts to solve real-world data problems, mastery of specialized Python tools and frameworks, and effective handling of large and complex datasets.
The course also addresses ethical considerations and encourages interdisciplinary approaches, preparing students for advanced roles in the data science industry and research environments. By building from foundational knowledge to advanced skills, covering everything from data preprocessing and model implementation to evaluation and deployment, this course equips students to deliver high-impact, innovative solutions in diverse data-driven domains.
Learning Tutorials: Streamlit - Web Apps for Machine learning and Advanced Data science
Streamlit by Prakash Ukhalkar.pdfGet started with Streamlit - Web Apps for Machine Learning and Advanced Data Science
Streamlit Guidelines for Google Colab.pdfRunning Streamlit App in Google Colab: A Step-by-Step Guide
Model Serialization with Pickle-Joblib.pdfModel Serialization with Pickle/Joblib: Saving and Loading Machine Learning Model
Exploratory Data Analysis (EDA) by Prakash Ukhalkar.pdfData Preprocessing and Exploration (EDA)
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