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Artificial Intelligence & Machine Learning

The AI & ML Internship Program is designed to give you practical, hands-on experience in developing intelligent systems using machine learning and deep learning. You’ll learn how to work with data, build predictive models, train neural networks, and apply industry tools like Scikit-learn, TensorFlow/Keras, Pandas, and more. The program also introduces version control (Git) and model deployment using Flask or Streamlit.

By the end of the internship, you'll be able to:

  • Build machine learning models for real-world datasets
  • Apply deep learning techniques for image or text data
  • Understand end-to-end AI/ML project workflows
  • Collaborate using Git and deploy models using simple web frameworks

 

Duration: 6 Weeks (6-8 hrs/week)                         Learning Format: Live/Online/Interactive  

Course Overview:

This internship provides a beginner-friendly, project-based learning experience in AI & ML. Interns gain hands-on exposure to supervised and unsupervised learning, neural networks, and model evaluation using Python based tools. The curriculum is designed to help interns transition into real-world data science and ML engineering roles, with a strong focus on practical skills and deployment-readiness.

Skills Developed:

  • Python for data analysis and machine learning
  • Data cleaning, preprocessing, and visualization
  • Supervised learning: regression, classification
  • Unsupervised learning: clustering, dimensionality reduction
  • Neural networks and CNNs using TensorFlow/Keras
  • Model evaluation and tuning (cross-validation, confusion matrix)
  • Version control using Git and GitHub
  • Model deployment with Flask/Streamlit
  • Resume building, mock interviews, and LinkedIn optimization

Course Curriculum

Duration: 6 Weeks

Level: Beginner to Intermediate

Goal: Equip interns with practical AI/ML skills for entry-level roles in data science or machine learning.

 Programming & Data Foundations

 Topics Covered:

  • Introduction to Artificial Intelligence & Machine Learning
  • Python Programming (Basics to Intermediate)
  • Data Analysis using:
    • NumPy
    • Pandas
  • Data Visualization:
    • Matplotlib / Seaborn
  • Basic Statistics:
    • Mean, Median, Variance, Correlation
  • Development Tools:
    • Jupyter Notebook / VS Code
  • Version Control:
    • Git & GitHub (Portfolio Setup)

 Projects:

  • Data Cleaning & Analysis Project (Netflix / IPL Dataset)
  • Data Visualization Dashboard

Machine Learning Fundamentals

 Topics Covered:

  • Introduction to Machine Learning Algorithms
  • Supervised Learning:
    • Linear Regression
    • Logistic Regression
    • Decision Trees
  • Model Evaluation Techniques:
    • Accuracy, Precision, Recall, F1 Score
  • Overfitting vs Underfitting
  • Feature Engineering & Data Preprocessing

 Projects:

  • Salary Prediction Model
  • Loan Approval Prediction System

Advanced Machine Learning

 Topics Covered:

  • Unsupervised Learning:
    • K-Means Clustering
  • Ensemble Techniques:
    • Random Forest
  • Introduction to Deep Learning
  • Recommendation Systems (Basics)
  • Kaggle Platform Introduction & Participation

 Projects:

  • Customer Segmentation System
  • Basic Recommendation Engine

AI Specializations

 Topics Covered:

  • Neural Networks Fundamentals
  • Frameworks:
    • TensorFlow / PyTorch (Introduction)
  • Computer Vision (Basics)
  • Natural Language Processing (NLP):
    • Text Processing
    • Sentiment Analysis
  • OpenCV (Basics)
  • Prompt Engineering (Working with Generative AI tools)

 Projects:

  • Image Classification Model
  • Sentiment analysis

Deployment & Career Readiness

 Topics Covered:

  • Model Deployment:
    • Flask / FastAPI
  • API Integration
  • Introduction to MLOps Concepts
  • End-to-End Project Development

 Final Capstone Project :

  • AI Resume Screening System
  • Stock Price Prediction Model
  • Fake News Detection System

 

 

HR & Career Skills Week

  • Professional Communication & Email Etiquette
  • Interview Prep & Mock Interviews
  • LinkedIn & Resume Optimization
  • Workplace Ethics & Time Management
  • HR Session: Understanding Roles in Tech Teams

Outcome: Build soft skills and career readiness for entry-level Salesforce roles.

 

 

₹10000   ₹12000 (17% off) Add to Cart

Course FAQs

A: No prior experience is required. The course starts with Python basics.

A: Yes. A certificate is awarded upon successful completion of the internship.

A: Yes. Interns complete a capstone project and multiple hands-on exercises.

A: Yes. Week 6 includes resume reviews, mock interviews, and career guidance.
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