Join us for a FREE hands-on Meetup webinar on Text Analysis with Azure AI Language Service (AI102) | Friday, December 20th, 2024 · 5:00 PM IST/ 7:30 AM EST Join us for a FREE hands-on Meetup webinar on Text Analysis with Azure AI Language Service (AI102) | Friday, December 20th, 2024 · 5:00 PM IST/ 7:30 AM EST
Search
Close this search box.
Search
Close this search box.

AI in Business: Strategies for a Data-Driven Future

Navigating AI’s Transformative Impact on Business Operations

Duration

1 Day (8 hours)

Level

Intermediate to Advanced Level

Design and Tailor this course

As per your team needs

Edit Content

Embark on a transformative journey into the realm of Artificial Intelligence (AI) with our one-day course, “AI in Business: Strategies for a Data-Driven Future.” This course is meticulously designed to equip stakeholders with a comprehensive understanding of AI’s capabilities and its strategic applications within the modern enterprise.

Participants will explore the critical roles of data collection, storage, and the synergy between Big Data, Data Science, and AI. Through engaging lectures and interactive discussions, attendees will gain the knowledge and skills necessary to evaluate various AI applications, including cloud-based and on-premise solutions. Additional insights into Generative AI and emerging trends in data analytics will prepare you for the evolving landscape of AI in business.

 

Outcomes:

By the end of this course, participants will possess a well-rounded understanding of AI’s practical applications and future potential in business settings. They will be empowered to make informed decisions regarding AI implementations and effectively collaborate across departments to drive AI initiatives forward.

Key Takeaways:

  • Insight into AI’s relevance and transformative potential in business
  • Knowledge of effective data collection and storage strategies
  • Understanding of the interplay between Big Data, Data Science, and AI
  • Skills to evaluate cloud-based vs. on-premise AI solutions
  • Familiarity with essential tools and technologies for AI implementation
  • Strategies for building and managing effective AI teams
Edit Content
  • C-suite executives
  • Business unit leaders
  • Product managers
  • Innovation strategists
  • Data analysts
  • IT managers
  • Project managers involved in data science initiatives
Edit Content
  • Overview of AI technologies (Machine Learning, NLP, etc.)
  • Key differences between traditional software and AI-driven solutions
  • How AI is reshaping industries: case studies from tech giants like Amazon, Nvidia, and Meta
  • Importance of data in fueling AI solutions
  • Building a data-driven culture in your organization
  • Big Data vs. Smart Data: Ensuring quality and relevance in data collection and usage
  • Using AI for predictive analytics and trend forecasting
  • Enhancing decision-making through real-time data insights
  • Case studies on AI-driven decision-making in various industries (e.g., finance, marketing)
  • Automating routine tasks and streamlining operations with AI
  • Implementing AI in customer service (e.g., chatbots, virtual assistants)
  • AI in supply chain optimization and operational improvements
  • Ethical considerations and responsible AI usage
  • Overcoming challenges in AI adoption (data privacy, bias, etc.)
  • How to develop a scalable AI strategy aligned with business goals
  • Identifying AI opportunities within your business model
  • Developing an AI roadmap: starting small and scaling effectively
  • Aligning AI initiatives with long-term business objectives
Edit Content
  • Basic understanding of business metrics and key performance indicators
  • Elementary data literacy
  • Fundamental knowledge of project management
  • General tech savviness

Connect

we'd love to have your feedback on your experience so far