{"id":"e9bf691c-8f88-4b57-b905-0e6186b34b95","title":"Machine Learning: Accelerator — Portfolio and Practice","description":"Machine Learning: Accelerator — Portfolio and Practice is aimed at working specialists and managers aged 25–44 who need a structured upgrade they can deploy at work quickly. The program includes 10 lessons and about 30 hours, with emphasis on course orientation and outcomes, core concepts and mental models, and tools, setup, and learning environment; the capstone is a agent workflow map produced with Gemini, prompt libraries and evaluation rubrics.","contentLanguage":"en","coverUrl":"/course-covers/machine-learning-accelerator-portfolio-and-practice-788dd92d-10c.webp","createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:51:44.621Z","durationSeconds":108000,"authorId":"0f449781-cbdb-440f-a04b-3ae5ac53a0be","rating":4.333333333333333,"reviewCount":6,"expectedLessonsCount":10,"trailerUrl":null,"faq":[{"answer":"Basic familiarity is recommended. The opening block quickly aligns terminology and tools, then moves straight into hands-on implementation.","question":"Do I need prior experience?"},{"answer":"A comfortable pace is 3–5 hours per week. In total, the course includes 10 lessons and about 30 hours of guided work.","question":"How much time should I set aside each week?"},{"answer":"You will finish with a agent workflow map plus reusable materials built around Gemini and prompt libraries.","question":"What will I finish the course with?"}],"learningOutcomes":null,"requirements":null,"levels":["advanced"],"firstLessonFreePreviewEnabled":false,"certificateEnabled":true,"isPlatformCourse":false,"pricingTiers":[{"id":"standard","name":"Standard","price":129,"features":[],"highlighted":true}],"minPricingTierPrice":129,"bonuses":[],"status":"READY","archivedAt":null,"categoryId":"869af918-d185-46b9-84fe-8c771c9f7b29","lessons":[{"id":"4a0ebd19-03a3-45fe-81aa-ec205d2be078","title":"Machine Learning: Accelerator — Portfolio and Practice — course orientation and outcomes","description":"Lesson 1 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through course orientation and outcomes and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":0,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"1ae67570-90d4-466d-ac96-11a3ecb3012f","title":"Machine Learning: Accelerator — Portfolio and Practice — core concepts and mental models","description":"Lesson 2 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through core concepts and mental models and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":1,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"a662a643-8aa1-4885-b110-029ce781adeb","title":"Machine Learning: Accelerator — Portfolio and Practice — tools, setup, and learning environment","description":"Lesson 3 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through tools, setup, and learning environment and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":2,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"a58524b6-4d90-4142-b6a1-659aa62cd11d","title":"Machine Learning: Accelerator — Portfolio and Practice — practical workflows and process design","description":"Lesson 4 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through practical workflows and process design and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":3,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"f3685c8f-37be-4828-b5b5-c6be1a81f6f5","title":"Machine Learning: Accelerator — Portfolio and Practice — real cases and guided practice","description":"Lesson 5 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through real cases and guided practice and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":4,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"ab7e7eef-6960-429b-84c3-03c40eefe093","title":"Machine Learning: Accelerator — Portfolio and Practice — evaluation, quality, and safety","description":"Lesson 6 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through evaluation, quality, and safety and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":5,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"a8394da0-2499-421e-ae65-8c49769308c2","title":"Machine Learning: Accelerator — Portfolio and Practice — project build and review","description":"Lesson 7 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through project build and review and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":6,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"438fafbb-a2f1-42b9-980d-32f42923d713","title":"Machine Learning: Accelerator — Portfolio and Practice — implementation, handoff, and next steps","description":"Lesson 8 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through implementation, handoff, and next steps and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":7,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"e1c848ea-3226-4550-b3e5-87a7cede6f48","title":"Machine Learning: Accelerator — Portfolio and Practice — security controls and risk reduction","description":"Lesson 9 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through security controls and risk reduction and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":8,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null},{"id":"59f21ce5-2588-4ec1-8c0f-f6ecf03b0dfe","title":"Machine Learning: Accelerator — Portfolio and Practice — data handling and preparation","description":"Lesson 10 of 10 in Machine Learning: Accelerator — Portfolio and Practice: work through data handling and preparation and turn the result into a reusable part of the final agent workflow map using Gemini and prompt libraries.","videoUrl":null,"videoFileName":null,"duration":10800,"position":9,"createdAt":"2026-05-26T07:47:04.471Z","updatedAt":"2026-05-26T07:47:04.471Z","courseId":"e9bf691c-8f88-4b57-b905-0e6186b34b95","attachments":null,"dripDelayDays":null,"isFreePreview":false,"previewStartSeconds":0,"previewEndSeconds":null,"prerequisiteId":null,"unlockAt":null,"availablePricingTierIds":null}],"author":{"id":"0f449781-cbdb-440f-a04b-3ae5ac53a0be","name":"Patrick Barnes","avatarUrl":"https://lernrise.com/public/avatars/teacher-avatars/en/be794c7c-9d1c-4f03-99c0-0c44abe9401a.webp","bio":null,"socialLinks":null,"isPlatformRepresentative":false},"hasTeamOffer":false,"teamOfferSummary":null}