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AI got cheap enough that Duolingo’s most expensive plan may not survive it. I read the earnings call transcript and opened the app to see what is actually changing for learners.
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Evaluate and prioritize projects, build integrated schedules with dependencies, govern resources and budgets, and apply quantitative risk and AI/ML tools in a capstone.
Develop executive presence, strategic thinking, financial acumen, and customer strategy while applying AI to decision-making, supply chain digital twins, and business transformation.
Learn product management end to end: define problems, deliver an MVP, write PRDs, handle technology and AI essentials, and launch with metrics, go-to-market and financial strategy.
Lead GenAI adoption across business functions: apply use cases in sales, customer service, software engineering and analytics, plus workflow automation, Microsoft Copilot, agentic AI and ethics.
Prepare for the CISSP certification exam with hands-on training in information systems security and build the expertise needed to pass with confidence.
Study the governance of digital technology: data flow and management, algorithms and AI policy, digital legislation and regulation, risk and security of digital systems, fintech, and policymaking.
Build AI products end to end: ideation and scoping, UX design, data strategy, model experimentation, prompt engineering, deployment and monitoring, roadmaps, and responsible AI.
Lead agentic AI product strategy: orchestrate multi-agent ecosystems, apply model context and tooling protocols, build agents on Azure with Copilot Studio and AutoGen, and design agentic UX.
Build secure full stack web applications with MongoDB, Express, React, Node.js and Java, deploy them on Azure, and speed up coding with GitHub Copilot and generative AI.
Automate software testing with Selenium, TestNG, Appium and Playwright, run API, load and performance tests, and apply generative AI and Power Automate RPA to test workflows.
Prepare for the TOGAF Foundation exam by mastering foundation-level enterprise architecture concepts covered in TOGAF certification training.
Build and deploy generative AI applications: prompt engineering, LLM app development, agentic frameworks with Model Context Protocol, image generation, GANs and VAEs, plus AI governance.
Build machine learning, deep learning, advanced generative AI, MLOps, NLP and intelligent control systems skills in Python through hands-on projects and a capstone.
Apply AI across business functions: build high-quality data pipelines, use applied machine learning, GenAI marketing and finance tools, ethical AI systems, and an AI-powered decision-making simulation.
Build enterprise defense skills across network security, cryptography, application security, malware and ransomware analysis, ethical hacking and VAPT, plus AI-powered red and blue team tactics.
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