Artificial Intelligence (AI) for Developers Training Course
Artificial Intelligence (AI) encompasses technologies that emulate human cognition within machines and applications, facilitating the creation of software that is more intelligent and adaptive.
This instructor-led training session, available online or at a dedicated facility, is designed for intermediate developers seeking to construct AI-enabled applications using practical tools and platforms. The curriculum is tailored to support government entities requiring specialized technical capacity building for government operations.
Upon completion of this program, participants will be equipped to:
- Grasp fundamental principles of AI and machine learning.
- Engineer AI capabilities utilizing Python and established libraries.
- Implement AI methodologies within existing software development initiatives.
- Assess model performance and deploy intelligent services.
Course Format
- Interactive lectures and structured discussions.
- Comprehensive exercises and practical application.
- Direct implementation experience within a live laboratory environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Course Outline
Overview of Artificial Intelligence
- Definitions and applications of AI
- Distinctions among AI, Machine Learning, and Deep Learning
- Key tools and platforms for government
Python Implementation for AI
- Refresher on Python fundamentals
- Operational use of Jupyter Notebook
- Installation and management of required libraries
Data Management and Preparation
- Procedures for data cleaning and preprocessing
- Application of Pandas and NumPy
- Data visualization techniques using Matplotlib and Seaborn
Foundations of Machine Learning
- Comparative analysis of supervised and unsupervised learning
- Core methods: classification, regression, and clustering
- Protocols for model training, validation, and testing
Neural Networks and Deep Learning Frameworks
- Principles of neural network architecture
- Utilization of TensorFlow or PyTorch environments
- Development and training of model systems
Natural Language Processing and Computer Vision
- Techniques for text classification and sentiment analysis
- Fundamentals of image recognition
- Application of pre-trained models and transfer learning
Deployment of AI Solutions in Applications
- Standards for saving and loading model assets
- Integration of AI models into APIs and web applications
- Best practices for system testing and ongoing maintenance
Summary and Strategic Next Steps
Requirements
- Competence in programming logic and structural design
- Hands-on experience with Python or comparable high-level programming languages
- Foundational knowledge of algorithms and data structures
Audience
- IT systems professionals
- Software developers seeking to integrate AI
- Engineers and technical managers exploring AI-based solutions
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
Michal Maj - XL Catlin Services SE (AXA XL)
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