Introduction to Python Lists Loops Comprehension Applied Ai With Python Batch 1 Class 1 Mohan Sivaraman
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From Python Function to API | Applied AI with Python Batch 1 · Class 27 | Mohan Sivaraman
User-Defined Functions in Python | Applied AI with Python Batch 1 · Class 4 | Mohan Sivaraman
Python Tuples & Sorting | Applied AI with Python Batch 2 · Class 11 | Mohan Sivaraman
Understanding a CSV with Pandas | Applied AI with Python Batch 1 · Class 8 | Mohan Sivaraman
Python Basics – print, import & pip | Applied AI with Python Batch 2 · Class 5 | Mohan Sivaraman
Dictionary Methods – pop() & items() | Applied AI with Python Batch 1 · Class 3 | Mohan Sivaraman
String & List Manipulation in Python | Applied AI with Python Batch 2 · Class 7 | Mohan Sivaraman
Exception Handling in Python | Applied AI with Python Batch 1 · Class 6 | Mohan Sivaraman
Python Dictionaries – Practice | Applied AI with Python Batch 2 · Class 10 | Mohan Sivaraman
Categorical to Numerical Conversion | Applied AI with Python Batch 1 · Class 10 | Mohan Sivaraman
Python Dictionary – Keys & Values | Applied AI with Python Batch 1 · Class 2 | Mohan Sivaraman
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Last Updated: November 9, 2026
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Summary
Comparing classification models on a loan-approval dataset, with preprocessing for skewed and numeric columns using pipelines ... What LLMs, RAG, embeddings and vector databases are, with a first hands-on look at LangChain, Hugging Face and FAISS. What web applications are, and how a plain Writing your own functions: arguments, return values, isinstance checks and importing functions across files, as used in real ... Exploring a dataset with Pandas: info, describe, shape, dtypes, categories, map and drop. Playlist: Removing data with pop(), working with JSON, String manipulation, type casting a string to a Hands-on dictionary practice: keys and values, updating and adding keys, mixed key types, and common pitfalls. Playlist: ... Converting categorical data to numbers with map() and scikit-learn preprocessing, and filling missing data with SimpleImputer.
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