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TTAI2130 is designed for professionals involved in developing, deploying, and managing technology solutions seeking to leverage AI and machine learning. Key roles that stand to gain significant benefits from the course include-
• Software Developers and Engineers responsible for constructing and maintaining software solutions and their relevant integration to AI and ML technologies.
• IT Managers and Project Managers involved in the technology projects at their organization. It equips them to navigate the successful integration and deployment of AI and ML within their organizational frameworks.
• Business Analysts and Operations Managers who are responsible for streamlining business processes at the organization, ensuring operations are running efficiently and productively.
• Test Engineers and Quality Assurance Analysts are responsible for ensuring that software and systems' work quality and reliability are delivered smoothly.
• Data Scientists and Analysts want to work with data to extract insights and inform data-driven decisions.
To excel in the course, learners and professionals are encouraged to meet the following prerequisites-
• Learners and professionals should have a fundamental understanding of technology systems integral to business operations. It is recommended to have a familiarity with software applications, networks, and databases.
• Learners are expected to be acquainted with interpretation and data analysis. They must have basic analysis skills and an understanding of how data is utilized for decision-making and predictions.
• It is recommended to have a robust problem-solving and critical-thinking skills. Learners should be able to adapt AI applications to formulate testing strategies and evaluate AI model performances within operational contexts.
Throughout this hands-on learning experience facilitated by our experts, you will achieve the following course objectives:
• Cultivate the ability to identify and evaluate potential AI applications
• Equip tools and techniques to implement AI systems responsibly
• Enhance operations within the organization
• Acquire skills needed to navigate the entire AI testing lifecycle
• Develop proficiency in designing and executing comprehensive test plans for AI systems
• Prepare test environments
• Master the process of evaluating AI model performance using key metrics
• Ensure successful integration and deployment of AI models in real-world operational environments
• Identify and evaluate potential AI applications
• Improve decision-making processes and strategies to optimize workflows
• Explore case studies of successful AI implementations
• Develop and validate stages for the deployment and monitoring of AI models
• Empower operational fit of AI models
• Handle AI system failures and updates
• Strike a balance between performance, complexity, and cost
• Develop a high-level understanding of security
• Reliability and quality of AI systems throughout their operational lifespan
• Mitigate potential risks and challenges associated with ethical considerations in AI
Virtual Instructor-Led Training
- Instructor led Online Training
- Experienced Subject Matter Experts
- Approved and Quality Ensured training Material
- 24*7 leaner assistance and support
Customized According To Team's Requirements
- Customized Training Across Various Domains
- Instructor Led Skill Development Program
- Ensure Maximum ROI for Corporates
- 24*7 Learner Assistance and Support
• What is AI?
• Types of AI: Narrow AI vs. General AI
• Popular AI and ML algorithms
• AI vs. Machine Le
• AI applications in various industries
• State of AI and ML today
• Future potential
• Recent advancements and limitations
• Operational use cases for AI
• Identifying potential AI applications in your organization
• Integrating AI into existing workflows
• AI-driven decision making
• Activity: Designing a test plan for a hypothetical AI application
• Case studies of successful AI implementations
• Overcoming common challenges during AI implementation and testing
• Test cases from real-world AI rollouts
• Activity: Identifying key testing milestones in an AI project
• Development, validation, and deployment phases
• Overview of the AI testing lifecycle
• Ensuring AI model quality and reliability
• Preparing the test environment
• Activity: Creating a test environment for a hypothetical AI application
• Monitoring AI system performance
• Types of tests for AI systems
• Handling AI system failures and updates
• Key performance metrics for AI models
• Determining the operational fit of AI models
• Activity: Evaluating a sample AI model using performance metrics
• Balancing performance, complexity, and cost
• Strategies for ensuring AI security and ethics
• Security concerns in AI implementations
• Ethical Considerations in AI and ML
• Continued learning resources
• Closing discussion and feedback
• How to stay updated on AI developments
• Online courses, books, and communities
AI Operations Engineer
AI Test Engineer
TTAI2130, Exploring AI Operations: Strategies For Testing And Deploying Intelligent Systems For Success, is a 02-day hands-on course.
The course code through which it can be accessed is TTAI2130.
Exploring AI Operations: Strategies For Testing And Deploying Intelligent Systems For Success is a 02-day hands-on course crafted with Vinsys, an expert-led course. The expert's assistance will help you enhance your learning through the hands-on lab sessions to acquire skills in AI in various business areas, AI testing lifecycles, AI and ML today, and more. Our experts have more than ten years of experience in the field, further ensuring that the lectures are meaningful. You will learn to leverage AI and ML effectively to produce results after enrolling in a course by Vinsys.
The course is suitable for those seeking to utilize AI and ML techniques for data analysis and prediction. This includes test engineers, quality assurance analysts, business analysts, operations managers, IT managers, project managers, data scientists, and analysts.
Designed with experts, the course can unlock the potential of AI application identification, navigating the AI testing lifecycles, evaluating model performance, and understanding security and ethical considerations. The course directly applies to enhance professional AI and machine learning capabilities.
Our courses are delivered through instructor-led training (ILT), private group training, and virtual instructor-led training (vLIT). We boost your odds of success by helping you prepare for required exams and earn the certification. Effective course material accessed throughout the program makes learning about concepts beyond the class easier. You can choose your learning path to upskill with Vinsys' subject matter experts upon customizing training needs to ensure 100% results.
The course will help the learners cover a range of topics, including identifying and evaluating AI applications, designing effective test plans, navigating the AI testing lifecycle, evaluating AI model performance, and understanding security and ethical considerations in AI. You will be able to apply for a diverse range of opportunities in the corporate world.
Yes, learners will have an opportunity to interact with the instructors till the time their confusion and queries are resolved. You can enjoy 24*7 support from Vinsys even after the course completion.
There are various options to choose from, including AI solutions architect, Computer vision manager, NLP engineer, data scientist, and more, which help you identify, resolve, analyze, and resolve vulnerabilities faster.