Python with Machine Learning Workshop – 40 Hours

Python with Machine Learning Workshop

Duration: 40 Hours
The Python with Machine Learning Workshop is a practical 40-hour programme designed for students who want to build strong skills in Python programming, data analysis, data visualization, machine learning algorithms, and real-world project development.
Participants will learn Python from the basics and gradually move towards working with datasets, training machine learning models, evaluating predictions, and building a complete mini project. The workshop is suitable for degree students, graduates, and beginners interested in Artificial Intelligence, Data Science, and Machine Learning.

Module 1: Introduction to Python, AI and Machine Learning

Duration: 3 Hours
Learn the basics of Python programming and understand Artificial Intelligence, Data Science, Machine Learning, and Deep Learning. Participants will also learn how Python is used in modern AI applications.
Practical Activity:
Install Python, Jupyter Notebook, or use Google Colab. Write and run basic Python programs.

Module 2: Python Programming Fundamentals

Duration: 8 Hours
Learn Python syntax, variables, data types, operators, input and output statements, conditional statements, loops, functions, strings, lists, tuples, sets, dictionaries, and basic error handling.
Practical Activity:
Create programs for student marks calculation, attendance management, calculator operations, menu-driven applications, and number-based logic problems.

Module 3: Object-Oriented Programming and File Handling

Duration: 4 Hours
Learn classes, objects, constructors, inheritance, encapsulation, and basic file handling in Python.
Practical Activity:
Create a student record management program using classes and files.

Module 4: Python for Data Analysis

Duration: 6 Hours
Learn how to use NumPy and Pandas for working with datasets. Topics include importing CSV files, viewing data, data cleaning, handling missing values, sorting, filtering, grouping, merging, and basic statistical analysis.
Practical Activity:
Import a real dataset and perform data cleaning, filtering, grouping, and analysis using Pandas.

Module 5: Data Visualization

Duration: 4 Hours
Learn to create meaningful charts and graphs using Matplotlib and Seaborn.
Practical Activity:
Create bar charts, line charts, pie charts, histograms, box plots, scatter plots, and correlation heatmaps.

Module 6: Machine Learning Fundamentals

Duration: 4 Hours
Understand the machine learning lifecycle, supervised learning, unsupervised learning, features, labels, datasets, training data, testing data, model prediction, overfitting, underfitting, and model evaluation.
Practical Activity:
Prepare a dataset, select features and labels, and perform train-test split using Scikit-learn.

Module 7: Machine Learning Algorithms

Duration: 7 Hours
Learn and implement important machine learning algorithms using Scikit-learn.
Algorithms Covered:

• Linear Regression
• Multiple Linear Regression
• Logistic Regression
• Decision Tree
• Random Forest
• K-Nearest Neighbors
• Naive Bayes
• K-Means Clustering

Practical Activity:
Train, test, compare, and evaluate multiple machine learning models using real datasets.

Module 8: Mini Project, Presentation and Assessment

Duration: 4 Hours
Participants will develop and present a machine learning mini project.
Project Options:

• Student Performance Prediction
• House Price Prediction
• Sales Prediction
• Customer Purchase Prediction
• Loan Eligibility Prediction
• Employee Salary Prediction
• Iris Flower Classification
• Customer Segmentation Using K-Means

Assessment Includes:

• Python coding assessment
• Dataset analysis
• Machine learning model demonstration
• Project presentation
• Viva and feedback

Pricing Structure

Workshop Duration: 40 Hours
Inhouse Workshop: ?2,500 per candidate
Onsite Workshop: ?1,500 per candidate
For a batch of 40 students:

• 40 × ?1,500 = ?60,000 for an onsite workshop
• 40 × ?2,500 = ?1,00,000 for an inhouse workshop

Batch Size Criteria

The batch size should be a minimum of 40 participants and a maximum of 60 participants.
For batches with fewer than 40 participants, workshop charges will be calculated on an hourly basis.