Engaging visual content to enhance understanding and learning experience.
Auto-GPT
Datapad
People.ai
Databricks
MindsDB
Dataiku (AI Agents)
FuseBase
Manus AI
Akkio
Perplexity
Transition from traditional dashboards to autonomous AI + Data Agents that act on real-time insights
Design and deploy goal-driven AI agents capable of planning, executing, and completing multi-step tasks
Query and analyze complex datasets using natural language interfaces without writing code
Build and manage predictive models for forecasting, lead scoring, and trend analysis
Orchestrate multi-agent systems to handle research, analysis, execution, and reporting workflows
Automate market research, competitor analysis, and enterprise data discovery
Implement Retrieval-Augmented Generation (RAG) for grounded, enterprise-grade AI responses
Integrate AI agents seamlessly into CRMs, data platforms, and existing business systems
Create no-code and low-code agentic workflows for rapid deployment across teams
Manage agent memory, prioritization, and asynchronous task execution
Build AI-powered enterprise knowledge bases and client-facing portals
Data analysts, business leaders, and anyone looking to automate data workflows with AI.
No. Most tools focus on "no-code" or "natural language" interfaces, though Python skills are a plus.
4–6 weeks of hands-on practice.
Many have free tiers or trials; the course covers both accessible and enterprise-level tools.
Yes, the assignments are designed to be applied to your real-world business data.