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Artificial Intelligence and Data Science Internship

AI and DS

The Artificial Intelligence and Data Science Internship is a comprehensive program designed to bridge the gap between academic learning and practical industry applications by offering participants in-depth exposure to cutting-edge technologies, methodologies, and tools.

This internship is designed to build strong foundations in areas such as machine learning, deep learning, natural language processing, computer vision, and big data analytics, while also covering essential tools like Python, TensorFlow, PyTorch, and SQL. Interns will gain exposure to end-to-end project workflows, including data collection, preprocessing, model development, evaluation, and deployment.

By the end of the internship, participants will be equipped with the knowledge, technical competence, and confidence required to pursue advanced roles such as data scientist, machine learning engineer, AI researcher, data analyst, or business intelligence specialist, making this program a transformative stepping stone toward a successful career in the ever-evolving world of artificial intelligence and data science.

AI and Data Science Internship Topics

Introduction to Artificial Intelligence & Data Science
 • Overview of AI, Machine Learning, and Data Science
 • Applications in healthcare, finance, IoT, and business

Python for Data Science
 • Python basics, libraries (NumPy, Pandas, Matplotlib)
 • Data preprocessing and visualization

Machine Learning Fundamentals
 • Supervised and unsupervised learning techniques
 • Regression, classification, and clustering

Deep Learning & Neural Networks
 • Introduction to TensorFlow and PyTorch
 • Building and training neural networks

Natural Language Processing (NLP)
 • Text preprocessing and sentiment analysis
 • Chatbots and real-time applications

Model Deployment & Real-World Projects
 • Deploying ML models with Flask
 • End-to-end AI project implementation

Deep Learning Models
 • Federated Learning
 • Multimodal Deep Learning
 • Transfer Learning
 • Quantum Machine Learning
 • Deep Reinforcement Learning
 • Few-Shot Learning

Tools and Technologies Used for AI and Data Science

Editor or Tools : Anaconda3 / Spyder 5.4.3 / Jupyter Notebook

Back-end Technologies : Python 3.11.1

Data Science Libraries : Scikit-Learn / Numpy / Pandas / Matplotlib / Seaborn

Deep Learning Frameworks : Keras / TensorFlow / PyTorch


AI

~ Internship Duration ~

Choose The Best AI and Data Science Internship
Service

Tools and Frameworks in AI and Data Science Internship

Python

Anaconda

Spyder

Jupyter Notebook

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