Select Language

Select Country

ENQUIRE NOW

Implementing AI In Business: Stakeholder Strategies For The Modern Data-Driven, Automated Enterprise (TTAI2101)

Strategic Approaches to AI Implementation Success

Gain strategic insights and elevate your business with AI innovation!
Implementing AI In Business: Stakeholder Strategies For The Modern Data Driven, Automated Enterprise (TTAI2101) is a 01-day course allowing you to immerse in the ever-evolving realm of AI to furnish stak

275

654 Partipants

Looking for Corporate Training

Click Here

Enroll Now

TTAI2101

training

Domain / Vendor

implementing ai in bussiness ttai2101 certification

Engage in the personalized learning experience.

Access 24/7 support during the course

Get unlimited post-program access to course material

Access specialized expert training resources

Overview Learning Objectives Who Should Attend Outline

Implementing AI In Business: Stakeholder Strategies For The Modern Data-Driven, Automated Enterprise (TTAI2101)

TTAI2101 goes beyond the fundamentals and course concepts, empowering you to make well-informed decisions across diverse AI applications. In this course, you will cover essential aspects of the AI implementation techniques, such as the significance of the collection and storing of data and unraveling the interdependence of workshops that are thoughtfully designed. Hand-on course experience will help you develop the ability to assess cloud-based versus on-premise solutions, comprehending crucial factors in forming effective data science. The course concepts will let you familiarize yourself with essential AI frameworks and tools.

Through captivating lectures and demonstrations, our experts ensure that you gain a well-rounded grasp of AI's practical application and its future potential. If you are seeking to enhance the existing system capabilities, then you must opt for the course as it ensures actionable insights required for a meaningful transformation at the organization. You will learn to explore the relevant impact of AI technologies in modern business while working under AI ethics and regulation. The course concepts will guide you toward the identification of the data types.

Objectives

Within our guided settings, you will gain the following course objectives:

Gain insights into data science and machine learning methods
Enhance Key Performance Indicators (KPIs) for AI
Efficient AI Project Lifecycle management
Gain knowledge to facilitate effective AI project guidance, ensuring smooth and iterative improvement
Empower to effectively lead AI initiatives
Acquire skills to proficiently manage the successful deployment
Grasp considerations involved in selecting data science and AI-driven systems
Optimal decision-making for cloud-based solution
Contribute to the enhancement of business operations
Maintain a competitive edge within the organization
Attain a thorough comprehension of AI
Learn to choose the right AI model for catering to the needs
Gain insights into the convergence of big data
Recognize the critical role of data in AI
Develop strategies to safeguard AI systems
Explore prevalent tools and technologies facilitating informed decision-making
Discerning their role in achieving business objectives
Cultivate a deep understanding of AI and data security practices to develop strategies and safeguard AI systems effectively
Strategic awareness of upcoming trends in AI
Plan and manage AI projects

Audience

TTAI2101 is an introductory-level course designed for individuals catering to a diverse range of business stakeholders within their organizations. The target audience of the course includes-

C-suite executives
Product Managers
Business unit leaders
Innovation strategists
IT professionals working as IT managers, project managers, data analysts, and managers who want to collaborate with data science teams.
Individuals are looking forward to efficient communication across their departments at the organization.

Course Outline

Module 1. Introduction to AI in Business

Explore the relevance and potential impact of AI technologies in modern businesses.
What is AI and Why Does It Matter
The ROI of AI Adoption
Case Studies: AI Transformations
AI Ethics and Regulation
AI's Role in Different Business Units
Real-World AI Transformations: A quick overview of businesses successfully adopting AI

Module 2. Data: The Bedrock of AI

Identify the types of data most pertinent to AI applications in business.
Types of Data: Structured vs Unstructured
Importance of Data Collection
Data Storage Solutions
Data Security and Compliance
Data Integration Strategies
Database Choices: Evaluating databases suited for AI applications

Module 3. Big Data, Data Science, and AI – The Power Trio

Explore how Big Data, Data Science, and AI synergize for business advantage.
The Big Data Ecosystem
Data Science Methodologies
Machine Learning vs Deep Learning
Business Cases for Data Science and AI
Tools for Analytics and Data Processing

Module 4. Cloud-Based vs. On-Premise Solutions

Make informed decisions on cloud-based vs. on-premise AI solutions.
Factors for Choosing a Platform
Cloud-Based Pros and Cons
On-Premise Pros and Cons
Cost Implications
Security Considerations
Cloud and On-Premise Comparison: Brief on performance, costs, and scalability

Module 5. Selecting Tools and Technologies

Explore various tools and technologies to facilitate AI adoption.
Popular AI Frameworks
Visualization Tools
Data Cleaning and Preprocessing Tools
Analytical Platforms
APIs and Libraries
Tool Showcase: Quick tour through a suite of cutting-edge AI tools

Module 6. Building Your Data Science and AI Teams

Explore the key skills and roles to consider when forming a data science/AI team.
Core Team Roles
Required Skill Sets
Training vs Hiring
Collaboration Tools
Team KPIs and Performance Metrics
Virtual Team Management: Leveraging tech for remote collaboration

Module 7. Generative AI: A New Paradigm for Business

Understand how Generative AI can redefine content creation, design, and decision-making in business.
What is Generative AI?
Applications in Marketing and Design
Generative AI in Product Development
Ethical and Legal Concerns
Generative AI in Business Strategy
Auto-Generated Content: See how Generative AI can automatically produce marketing copy and design elements

Module 8. Emerging Trends in Data & AI for Business

Stay ahead of the curve by understanding upcoming trends that will shape the future of AI in business.
Federated Learning and Edge AI
AI for Sustainability and Social Good
AI in Cybersecurity
Reinforcement Learning in Business
Explainable AI (XAI)
Explore the impact of new trends on different business sectors

Module 9. Next Steps and Action Plan

Develop a roadmap to start or advance AI implementation in your organization.
Setting Short-term and Long-term Goals
Budget and Resource Allocation
Scaling AI Projects
Ongoing Training and Skills Update

Choose Your Preferred Mode

Online Training

Instructor led Online Training
Experienced Subject Matter Experts
Approved and Quality Ensured training Material
24*7 leaner assistance and support

Enroll Now

Corporate Training

Customized Training Across Various Domains
Instructor Led Skill Development Program
Ensure Maximum ROI for Corporates
24*7 Learner Assistance and Support

Enroll Now

FAQ’s

What is the course duration?

Implementing AI In Business: Stakeholder Strategies For The Modern Data Driven, Automated Enterprise (TTAI2101) is a 01-day course.

What is the course code to access Implementing AI In Business?

The course code through which it can be accessed is TTAI2101.

Why should I enroll in this course by Vinsys?

Implementing AI In Business: Stakeholder Strategies For The Modern Data Driven, Automated Enterprise with Vinsys is an expert-led course. Our experts have more than ten years of experience in the field, further ensuring that the lectures are meaningful. The expert's assistance will help you enhance your learning through the hands-on lab sessions to acquire skills in AI Transformations, AI Ethics, AI applications, and more.

Can a beginner enroll in this course?

Absolutely! Whether you are new to the field of AI in Business or have basic business operations experience, this introductory-level course provides a solid foundation that offers valuable insights. Professionals have the upper hand in the course because they have experience in the world of AI Business.

Who should do this course?

Designed with experts, the course can unlock the potential of AI potential for C-suite executives, project managers, architects, IT leaders, business analysts, and individuals engaged in decision-making processes and enabling efficient communication across different departments.

How is the course program carried out at Vinsys?

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. Our courses are delivered through instructor-led training (ILT), private group training, and virtual instructor-led training (vLIT). You can choose your learning path to upskill with Vinsys' subject matter experts upon customizing training needs to ensure 100% results.

How will this course help the learners?

Through the course, learners will be able to dive deep into the AI principles and their comprehensive understanding to integrate its power into the organization. The learners will be able to build a capable AI team, make informed decisions on cloud-based vs. on-premise AI solutions, secure their AI systems, and drive the adoption of AI in the organization.

Can learners interact with the instructors?

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.

What are the job opportunities after AI?

There are a variety of options to choose from, including Data Scientists, Prompt Engineer, Machine Learning Engineer, Business Intelligence Developer, and more.

What industries are most impacted by Generative AI?

Banking, Life Sciences, and High-Tech industries are among those that are most affected by the percentage of revenues from Generative AI.