Python for AI: Basics with NumPy & Pandas
Course provided by Model Institute of Engineering & Technology
5 modules
Explore the fundamentals of Artificial Intelligence & Machine Learning
4.5 Level NCrF
National Credit Framework
30 Hours
Flexible Learning
Beginner Level
No prior experience required
Nano Credit Course
01 Credit
Course Overview
This course introduces students to Python programming essentials with a focus on data handling and analysis. Learners gain practical experience using NumPy for numerical operations and Pandas for managing and analyzing structured data. Through hands-on exercises and a mini project, students build a strong foundation for applying Python in real-world AI and data science tasks.
Key Learning Highlights
Gain hands-on experience with Python programming fundamentals.
Master NumPy for array creation, indexing, slicing, and mathematical operations.
Learn to use Pandas for effective data wrangling and tabular data analysis.
Perform exploratory data analysis (EDA) using descriptive statistics and data visualization.
Work on a mini project involving real-world datasets for cleaning and analysis.
Tools & Platform Used
Python 3.x
Core programming language
NumPy
Numerical computations and array operations
Pandas
Data wrangling and analysis
Learning Outcome
By the end of this course, students will be able to:
Understand Python fundamentals relevant to Artificial Intelligence.
Manipulate and analyze data using NumPy and Pandas.
Perform exploratory data analysis (EDA) with descriptive statistics and visualizations.
Clean, filter, and transform real-world datasets for practical AI applications.
Apply coding-first approach to solve structured data problems with industry-standard libraries.
Master the course with just 5 Modules
The course is thoughtfully divided into five well-structured modules, making learning simple, engaging, and outcome-oriented. Starting with Python programming essentials, you’ll gradually move towards data manipulation, numerical operations, and exploratory data analysis using industry-standard libraries.
Python Essentials
Understand Python syntax, variables, and data types.
Work with loops and conditional statements.
Perform basic input/output operations.
NumPy Arrays and Operations
Create and manipulate arrays efficiently.
Apply slicing, indexing, and broadcasting.
Perform mathematical and statistical operations.
Introduction to Pandas
Work with Series and DataFrames.
Handle data input/output and selection.
Perform indexing, filtering, and basic transformations.
Exploratory Data Analysis
Summarize and aggregate data effectively.
Handle missing values in real datasets.
Visualize data using Matplotlib and Seaborn.
Mini Project – Data Cleaning and Analysis
Apply data cleaning techniques on real-world data.
Transform and preprocess datasets for analysis.
Generate insights through exploratory analysis.
Roles
- Python Programmer.
- Data Analyst (Entry-Level)
