Complete AI Course Artificial Intelligence
Summary
This diploma program provides a complete foundation in Artificial Intelligence (AI) and Machine Learning (ML). Students will learn programming with Python, data science concepts, machine learning algorithms, deep learning, natural language processing, and computer vision. The course is designed for beginners as well as IT professionals who want to build AI-driven solutions and gain hands-on experience with real-world projects.
By the end of the diploma, students will be able to develop, train, and deploy AI models in multiple domains such as business, healthcare, finance, and automation.
Course Content
Module 1: Introduction to AI & ML
- History and evolution of AI
- AI vs. ML vs. Deep Learning
- Applications in daily life and industries
- Ethical considerations in AI
Module 2: Python Programming for AI
- Python basics and advanced concepts
- NumPy, Pandas, Matplotlib, Seaborn
- Working with datasets and data cleaning
- Practical coding exercises
Module 3: Data Science Essentials
- Data preprocessing and feature engineering
- Exploratory Data Analysis (EDA)
- Data visualization techniques
- Handling large datasets
Module 4: Machine Learning Fundamentals
- Supervised & Unsupervised Learning
- Regression and Classification models
- Decision Trees, SVM, Naive Bayes, KNN
- Model evaluation and performance metrics
Module 5: Deep Learning & Neural Networks
- Basics of neural networks
- TensorFlow and PyTorch introduction
- CNNs for image recognition
- RNNs and LSTMs for sequential data
Module 6: Natural Language Processing (NLP)
- Text preprocessing techniques
- Sentiment analysis
- Word embeddings & transformers
- Chatbots and text classification projects
Module 7: Computer Vision Applications
- Image preprocessing and augmentation
- Object detection and recognition
- Transfer learning for vision tasks
- AI image classification project
Module 8: Reinforcement Learning
- Fundamentals of RL
- Q-Learning concepts
- Deep Q-Networks (DQN)
- Applications in robotics and gaming
Module 9: AI Tools & Frameworks
- Scikit-learn for ML
- TensorFlow, PyTorch, Keras
- Hugging Face for NLP models
- OpenCV for vision projects
Module 10: AI in Industry
- AI in healthcare, finance, and business
- AI for automation and predictive analytics
- Case studies from real-world projects
- Future of AI careers
Module 11:
- Project
Requirements
- Minimum Intermediate (XII / A-Levels)
- Basic math knowledge (no coding needed, Python taught)
Who Can Join: Students, job seekers, IT professionals, and freelancers interested in AI & ML.
Certification:
Certificate of Completion by Educad Academy
International Student Fee: 950 USD
Flexible Class Options
- Corporate Group Training | Fast-Track
- Weekend Classes For Professionals SAT | SUN
- Online Classes – Live Virtual Class (L.V.C), Online Training
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