Dive into Learning Explore the rich courses offerings of MammothClub.

Test your knowledge of the generative AI (gen AI) landscape and its business impact! Including the core layers of gen AI—infrastructure, models, platforms, agents, and applications—and how each layer influences scalability, cost, performance, flexibility, and real-world business outcomes.

This course introduces students to Google Antigravity, an agent-first, AI-powered development environment designed to streamline and change the way applications and websites are built. Students explore what Antigravity is, how it differs from traditional IDEs and code assistants, and how to install and configure the platform for practical use.

Learn how to design and deploy powerful no-code virtual assistants using Make.com. In this course, you’ll discover how to combine Make with AI tools, APIs, and messaging platforms to build smart, responsive assistants that handle tasks like scheduling, lead capture, customer support, content generation, and more. Whether you're building for personal productivity or business automation, this course gives you the skills to create scalable, AI-powered assistants—no coding required.

Ready to step into a leadership role in the AI revolution? This is your straightforward no fluff roadmap to passing your certification and gaining the strategic edge needed to navigate the world of AI with confidence.

Stop manual prospecting and let the bots find your next client. Automate your sales pipeline now.

Test your knowledge of core generative AI (gen AI) concepts and use cases! Including core gen AI fundamentals such as artificial intelligence, machine learning, natural language processing, large language and foundation models, multimodal and diffusion models, and prompt engineering; key machine learning approaches like supervised, unsupervised, and reinforcement learning; the machine learning lifecycle and supporting Google Cloud tools; selecting the right foundation model for business needs; real-world gen AI use cases for creating, summarizing, discovering, and automating content; and the role of data types, data quality, accessibility, and the differences between structured vs. unstructured and labeled vs. unlabeled data.