Intro to Artificial Intelligence (AI) Training
- Online (Microsoft Teams)
- +971 562069465
- info@velosiaims.com
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Artificial Intelligence (AI) training involves acquiring the knowledge and skills required to work with AI technologies. The course typically covers a range of topics to provide participants with a comprehensive understanding of AI concepts, techniques, and applications.
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By the end of this course, participants should be able to:
- Understand the definition, history, and evolution of artificial intelligence.
- Explain the principles of supervised learning, including regression and classification.
- Learn how to select the right algorithm for a certain task.
- Understand the concept of Deep learning
- Utilize NoCode AI development tools using DataRobot
- Learn how to evaluate ML models
- Recognize ethical considerations in AI development.
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Training will be conducted via Microsoft Team Meeting. Meeting invites will be shared on the day before the first day of training.
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- 2 days (12 hours)
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- Presentation Slides
- Training Recordings
- Study References
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Upon successful completion of training, participants will receive a certificate.
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This course is appropriate for a wide range of professionals but not limited to:
- Software Developers and Programmers
- Engineers and Technologists
- IT Professionals
- Business Analysts and Managers
- Entrepreneurs
- Researchers and Academics
- Students and Recent Graduates
- Anyone Interested in AI
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- Basic knowledge of computer science concepts, including algorithms and data structures, is beneficial. This knowledge provides a solid foundation for understanding AI algorithms and models.
- Familiarity with data analysis concepts and tools is useful. Participants should understand how to work with datasets, manipulate data, and perform basic statistical analysis.
- While not always required, having a basic understanding of machine learning concepts is beneficial. Familiarity with supervised and unsupervised learning, as well as key evaluation metrics, provides a good starting point.
- Participants should possess critical thinking skills and the ability to approach problems analytically. AI often involves solving complex problems, and these skills are crucial for effective AI development.
- A genuine interest in AI and a curiosity to explore and learn new concepts is essential. AI is a rapidly evolving field, and participants should be motivated to stay updated on the latest developments.
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Participants can avail a discount of either an early bird or group discount whichever is higher with an additional discount when signing up for 2 or more courses.
Group Discount (same company only)
- 15% Discount for groups of 5 or more
- 10% Discount for groups of 3-4
Bundle Discount
- Sign up for 2 courses and get an extra 10% off
- Sign up for 3 courses and get an extra 15% off
Course Outline
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Module 1: Introduction to AI
1.1 Definition and History of AI
- What is AI?
- Historical development and milestones in AI.
1.2 AI Applications
- Overview of AI applications in various industries.
- Case studies showcasing AI success stories.
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Module 2: Machine Learning Fundamentals
3.1 Supervised Learning
- Regression and classification.
- Model training and evaluation.
3.2 Unsupervised Learning
- Clustering and dimensionality reduction.
- Case studies and applications.
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Module 3: Deep Learning
3.1 Neural Networks
- Fundamentals of neural networks.
- Activation functions, layers, and architectures.
- Demonstration using Teachable machine
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Module 4: Data Robot NoCode AI tool
4.1 Overview about DataRobot tool
- NoCode AI workflow
- Creating account for DataRobot
- Creating Regression, Classification and NLP model using DataRobot.
- Model Deployment
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Module 5: AI Ethics and Bias
5.1 Ethical Considerations in AI
- Responsible AI development.
- Case studies on ethical dilemmas.
5.2 Bias in AI
- Understanding and mitigating biases in AI models.
- Fairness in AI applications.