3-Month Artificial Intelligence Internship
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3 Month Artificial Intelligence Internship Program
Duration: 3 Month
Prerequisites: Basic programming knowledge (preferably Python)
Week 1: Foundations of AI and Python for Data Handling
- Introduction to AI Concepts:
- Overview of AI, Machine Learning (ML), and Deep Learning (DL)
- Applications of AI across various industries and types of AI
- Python for AI Development:
- Basic Python programming: data structures, control flow, and functions
- Introduction to essential libraries (Numpy, Pandas) for data manipulation
- Data Preprocessing and Visualization:
- Data cleaning techniques, data normalization, and handling missing values
- Basic data visualization using Matplotlib and Seaborn
Week 2: Machine Learning Basics
- Supervised Learning:
- Understanding linear regression for continuous data prediction
- Logistic regression for binary classification tasks
- Implementing models with scikit-learn
- Model Evaluation and Optimization:
- Evaluating model performance with metrics like accuracy, precision, recall, and F1 score
- Train-test split, cross-validation, and hyperparameter tuning for model improvement
Week 3: Introduction to Neural Networks and Deep Learning
- Basics of Deep Learning and Neural Networks:
- Understanding neural networks and the fundamentals of deep learning
- Building and training a simple neural network with TensorFlow and Keras
- Convolutional Neural Networks (CNNs) for Image Data:
- Introduction to CNNs and their application in image recognition
- Building and training a basic CNN model for image classification
Week 4: Advanced AI Applications and Project Development
- Natural Language Processing (NLP):
- Basics of NLP, text processing, and sentiment analysis
- Implementing simple NLP tasks using libraries like NLTK and SpaCy
- Reinforcement Learning (RL):
- Introduction to RL principles and basic applications
- Implementing a simple Q-learning model
- Capstone Project:
- Choosing a project (e.g., image classifier, chatbot, sentiment analysis model)
- Data gathering, model building, training, and evaluation
- Project documentation and presentation to conclude the internship
2nd Month – Internship Project
3rd Month: Project work and Placement Preparation
Course Content
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