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Learn a skill. Earn a certificate. Add it to your resume. Data science, generative AI, project management, cybersecurity, business, design, and more — there's a certificate for every career goal.
Build AI products end to end: ideation and scoping, UX design, data strategy, model experimentation, prompt engineering, deployment and monitoring, roadmaps, and responsible AI.
Study AI and business analytics through modules on present-day essentials, applied uses in the world, and emerging ideas, finishing with a final project.
Build NLP models in PyTorch: implement gradient descent, backpropagation and dropout, train CNNs and LSTMs, and fine-tune BERT and DistilBERT with Hugging Face.
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.
Analyse external business environments, adapt strategy in dynamic contexts, and decide under uncertainty, applying AI to customer centricity, STP, competitive priorities, and business for impact.
Apply analytics and AI to management decisions: analytics tools and techniques, advanced analytics, Gen AI-powered business case studies, privacy, ethics and risk, plus a capstone project.
Examine the promises and risks of generative AI: its use cases and limits, impacts on business, society, the environment and labor, and emerging governance and regulation.
A Machine Learning Engineer designs, builds, and productionizes ML systems to solve business challenges.
This learning path, designed for intermediate to advanced technical learners, offers on-demand courses to specialize in AI Infrastructure on Google Cloud.
Combine project management with GenAI tools and agile methods to prioritize work, manage project risks, lead distributed teams, and make ethical leadership decisions.
Explore how businesses use Google Cloud data, machine learning, and AI to transform their business models, and how to modernize infrastructure and applications.
Lead AI-driven finance transformation: apply GenAI to FP&A and predictive analytics, corporate investment decisions, risk, compliance and fraud analytics, and treasury and working capital.
Learn how AI and machine-learning systems are attacked and defended using MITRE ATLAS, the OWASP LLM Top 10, and the NIST AI RMF.
Examine the rise of algorithms and their limitations, fairness and bias in machine learning, and privacy and security concerns, then apply them across three projects.
Learn how artificial intelligence, cloud computing, and data analytics reshape business, and build a digital transformation strategy for your own organization.
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