Python & AI/ML Deep Learning Internship Program
A hands-on 2-month internship program to master Python, Machine Learning, Deep Learning, and Web Development by building 3 real-world AI-powered projects.
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About this Course
This intensive internship program is designed for beginners and intermediate learners who want to break into the world of Artificial Intelligence and Machine Learning using Python. Students will progress from Python fundamentals to advanced Deep Learning concepts including CNNs and NLP, guided through structured weekly modules. The program integrates web technologies like HTML, CSS, Flask, and SQLite to help learners build and deploy fully functional AI-powered web applications. With a strong focus on project-based learning, each student will complete 3 industry-relevant projects that simulate real workplace challenges. By the end of the program, graduates will have a job-ready portfolio and the confidence to work on AI/ML roles in the tech industry.
What you'll learn
Available Batches
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INTERNSHIP MAY BATCH - 2026
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Course Curriculum
- Python setup, variables, data types, input/output
- Conditions, loops (for, while), break/continue
- Functions
- Lists, tuples, sets, dictionaries
- File handling, exception handling
- HTML basics
- HTML Tags
- forms, tables, divs, semantic tags
- CSS basics — selectors, flexbox, basic styling
- Flask intro — routes, templates, Jinja2
- SQLite with Python — CREATE, INSERT, SELECT, UPDATE
- Flask + SQLite integration — full CRUD mini app
- NumPy — arrays, operations, indexing
- Pandas — DataFrames, cleaning, groupby, merging
- Matplotlib & Seaborn — plots, heatmaps, charts
- Scikit-learn basics — preprocessing, train/test split
- Linear Regression & Logistic Regression (hands-on)
- Decision Trees & Random Forest
- SVM, KNN, Naive Bayes
- Model evaluation — accuracy, confusion matrix, ROC
- Feature engineering, scaling, encoding
- PROJECT 1 START — Student Result Predictor (ML + Flask + SQLite)
- Neural networks — perceptron, layers, activation functions
- TensorFlow / Keras setup, building first ANN
- Forward pass, backpropagation, loss, optimizers
- ANN for classification (Iris / Titanic dataset)
- PROJECT 1 COMPLETE — Deploy on Flask with HTML/CSS UI
- CNN — conv layers, pooling, filters explained
- Image preprocessing with OpenCV
- 3Build CNN model — image classification
- PROJECT 2 — Face Mask / Object Detection Web App (CNN + Flask + HTML/CSS)
- NLP basics — tokenization, stopwords, stemming
- TF-IDF, Bag of Words, word vectors
- Sentiment Analysis with ML
- Intro to Transformers & Hugging Face
- ROJECT 3 START — AI Chatbot / Sentiment Analyzer (NLP + Flask + SQLite)
- Complete Project 3 backend + Flask API
- Build HTML/CSS frontend for Project 3
- SQLite — store user queries & responses
- Testing, debugging, code cleanup
- Final Presentation + Portfolio Review
Facilities Provided
Quick Info
- LevelIntermediate
- Duration60+ hours
- Learners780+
- Rating★ 5.0
- Certificate✅ Yes
- Internship❌ No
- Placement❌ No