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Data Science
Data science, analytics, and statistical modeling
Certificates
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CertificatePurchase+710 Modules OxMLMLx Fundamentals 25
This program offered a comprehensive 18-hour course that included theory and practical sessions covering key areas in modern machine learning, such as Introduction to ML, Deep Learning & Representation Learning, Optimisation, and Generative AI (vision & NLP).
Artificial IntelligenceData Science
CertificatePurchase+1216 Modules OxMLMLx Health & Bio 25
This program offered a comprehensive 23-hour course that included overview of machine learning theory in Representation Learning, Geometrical Deep Learning, Large Language Models, and Computer Vision, with in-depth applications in health and biomedical domains, including drug discovery, genomics, electronic health records, medical imaging, and clinical NLP
Artificial IntelligenceData Science +1
CertificatePurchase+1315 Modules OxMLMLx Representation Learning & Generative AI 25
MLx Representation Learning & Generative AI 25 is currently ongoing! We aim to have the recordings uploaded here around a couple days after the lectures are finished.
Artificial IntelligenceData Science
CertificatePRO10 Modules 100 Questions AI4GGStatistical Machine Learning
Master the mathematical foundations and statistical methods underlying modern machine learning. This certification covers probability theory, Bayesian modeling, optimization, and advanced statistical inference techniques essential for rigorous ML research and development.
Artificial IntelligenceData Science
CertificatePRO10 Modules 100 Questions AI4GGRepresentation Learning
Explore cutting-edge techniques for learning powerful data representations. This certification covers self-supervised learning, transformers, multimodal models, and generative AI, preparing you for advanced roles in modern deep learning and foundation model development.
Artificial IntelligenceData Science
CertificatePRO14 Modules 100 Questions AI4GGEvals for AI Products — from model.fit() to market.fit()
This learning plan covers the full landscape of evaluation for AI systems, moving from classical machine-learning diagnostics to the challenges of modern generative, agentic, multimodal, and enterprise-scale deployments. Learners progress through foundational metrics, LLM and agent evaluation, multimodal testing, domain-specific benchmarks, operational and safety assessments, and commercial ROI evaluation. By the end, participants can design rigorous eval suites that reflect scientific best practices, real-world constraints, and business outcomes. The course blends technical depth with practical workflows that are essential for trustworthy, high-impact AI products.
Artificial IntelligenceData Science +1
Jobs
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Role12 Modules 55 Questions GRMachine Learning Researcher
A comprehensive 12-week learning plan designed to prepare for both AWS Certified Machine Learning – Specialty (MLS-C01) and Google Cloud Professional Machine Learning Engineer certifications. This plan follows an overlap-first approach, covering shared ML concepts before addressing platform-specific differences. It includes diagnostic assessment, optional refresher tracks, hands-on labs using free-tier resources, research-oriented practices, and a 2-week exam simulation phase. Structured for part-time study alongside work with emphasis on applied practice, MLOps, and exam readiness.
Artificial IntelligenceCloud Computing +1
Role12 Modules 165 Questions GRData Vendor Analyst
A comprehensive 12-week cohort-based learning plan designed to prepare teams for the ISM Certified Professional in Supply Management (CPSM) certification exam while building practical skills for Data Vendor Analyst and Vendor Management Analyst roles. This plan integrates CPSM exam content (165 multiple-choice questions, 180 minutes, 70% passing score) with hands-on practice in vendor scorecards, SLAs/KPIs, contract management, sourcing, negotiations, supplier relationship management, risk/compliance, Excel, SQL, data quality, governance, and reporting. Includes diagnostic assessments, progressive content modules, practice quizzes, scenario-based assignments, and a final review week with mock exam. Structured for weekly cohort delivery with facilitator guidance and differentiated pathways for beginner and intermediate learners.
Data Science
Role13 Modules 180 Questions GRQuantitative Researcher
Template plan to prepare a team for a Quantitative Researcher – Fundamental Equity Research role, aligned to CFA Program Level I exam readiness while building practical quant equity research capabilities (factor research, backtesting, portfolio construction, risk, and research communication). Rolling cadence (no fixed exam date) with diagnostics, projects, question-bank routines, and mock exams.
Data ScienceFinance
Role11 Modules 60 Questions GRMachine Learning Engineer
Template plan to prepare a team for ML Engineer responsibilities and the Google Professional Machine Learning Engineer certification. Includes a core 6–8 week sprint and an extended 12–16 week track, with hands-on labs/projects, practice exam cadence, and an optional multi-cloud mapping module (AWS/Azure). Fill in placeholders for team size, weekly time budget, and cloud access.
Artificial IntelligenceCloud Computing +1