Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AI and ML
- Overview of AI and ML concepts
- Data collection and preprocessing
- Introduction to Python for AI
Data Analysis and Visualization
- Exploratory data analysis
- Data visualization techniques
- Statistical foundations for ML
Machine Learning Models
- Supervised learning algorithms
- Unsupervised learning algorithms
- Model evaluation and selection
Deep Learning and Neural Networks
- Fundamentals of neural networks
- Convolutional neural networks (CNNs)
- Recurrent neural networks (RNNs)
Natural Language Processing (NLP)
- Text processing and feature extraction
- Sentiment analysis and text classification
- Language models and chatbots
Computer Vision
- Image processing fundamentals
- Object detection and image classification
- Advanced topics in computer vision
Deployment and Scaling
- AI application deployment strategies
- Scaling AI applications
- Monitoring and maintaining AI systems
Ethics and Future of AI
- Ethical considerations in AI
- AI policy and regulation
- Future trends in AI and ML
Lab Project
- Developing a small-scale intelligent application
- Working with real-world datasets
- Collaborating on a group project to solve an industry-relevant problem
Summary and Next Steps
Requirements
- An understanding of basic programming concepts
- Experience with Python and fundamental data science techniques
- Familiarity with core AI and ML principles
Audience
- AI professionals
- Software developers
- Data analysts
28 Hours