Data Analysis Course in Mumbai

Introduction to Data Analysis and its real-world applications

Setting up the environment for data analysis (Python, Jupyter Notebook, libraries like Pandas, NumPy)

Loading and exploring datasets using Python

Understanding data types, structures, and basic operations in data analysis

Writing your first data analysis script with Pandas

Declaring variables for storing and analyzing data

Data types in data analysis (integers, floats, strings, booleans, objects)

Performing arithmetic, logical, and comparison operations on data

Typecasting and converting between data formats (e.g., string to datetime)

Using conditional statements (if, elif, else) to apply logic in data transformations

Leveraging comparison and logical operators for filtering data

Looping through datasets using for and while loops

Controlling loop execution using break and continue in data cleaning and analysis

Introduction to lists and basic manipulation for data grouping

Exploring tuples and their immutability in data processing

Understanding dictionaries for working with key-value structured data

Accessing, updating, and iterating through data collections efficiently

Creating and invoking user-defined functions

Understanding parameters and return values

Overview of Python’s built-in functions and standard libraries

Importing external modules and using them effectively in projects

Reading from and writing to text and binary files

Handling runtime errors using try-except blocks

Working with file objects and understanding file modes (r, w, a, etc.)

Performing basic file operations (create, delete, rename, read, write)