python

Explore in-depth topics and key concepts in data-analytics — e.g., Strings and Lists, Python Programming, NumPy and PyTorch Fundamentals, Working with Dataframes in Pandas.

Topics Covered

Strings and Lists

Key Concepts: string manipulation, list operations, indexing and slicing

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Python Programming, NumPy and PyTorch Fundamentals

Key Concepts: Introduction to Python, Data types and variables, Control structures (if statements, loops), Functions and modules, Introduction to NumPy arrays, Basic operations with NumPy, Introduction to PyTorch tensors, Basic operations with PyTorch

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Working with Dataframes in Pandas

Key Concepts: Creating DataFrames, Indexing and Selecting Data, DataFrame Operations, Merging and Joining DataFrames

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Introduction to Pandas DataFrames

Key Concepts: Understanding DataFrames, Series, and basic operations

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Tuples and Lists

Key Concepts: Definition and characteristics of tuples, Creating and accessing tuples, Immutability of tuples, Lists vs. tuples, Creating and manipulating lists, Common list methods

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Understanding Strings, Lists, and Tuples

Key Concepts: Introduction to Strings in Python, String Manipulation and Methods, Introduction to Lists and Their Properties, List Operations and Methods, Understanding Tuples and Their Uses

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Introduction to Strings in Python

Key Concepts: What are strings, Creating strings, String indexing and slicing, String methods

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Dictionaries and Working with Pandas DataFrames

Key Concepts: Introduction to Dictionaries in Python, Dictionary Operations and Methods, Introduction to Pandas and DataFrames, Loading and Exploring Data with Pandas Basic , Data Manipulation with Pandas

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Introduction to Machine Learning Models (Regression & Decision Trees)

Key Concepts: Introduction to Linear Regression, Implementing Linear Regression in Python, Understanding Logistic Regression, Implementing Logistic Regression in Python, Introduction to Decision Trees and Their Use Cases

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