このコースについて

18,975 最近の表示
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限
スケジュールに従って期限をリセットします。
約13時間で修了
英語
字幕:英語
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限
スケジュールに従って期限をリセットします。
約13時間で修了
英語
字幕:英語

提供:

Alberta Machine Intelligence Institute ロゴ

Alberta Machine Intelligence Institute

シラバス - 本コースの学習内容

1

1

4時間で修了

Machine Learning Strategy

4時間で修了
8件のビデオ (合計42分), 1 reading, 7 quizzes
8件のビデオ
ML Readiness6 分
Risk Mitigation5 分
Experimental Mindset5 分
Build/Buy/Partner7 分
Setting up a Team5 分
Understanding and Communicating Change7 分
Weekly Summary2 分
1件の学習用教材
IP questions10 分
6の練習問題
ML Readiness Review10 分
Risk Mitigation Review10 分
Experimental Mindset Review10 分
Build/Buy/Partner Review30 分
Setting up a Team Review5 分
Communicating Change Review5 分
2

2

2時間で修了

Responsible Machine Learning

2時間で修了
6件のビデオ (合計27分)
6件のビデオ
Positive Feedback Loops & Negative Feedback Loops6 分
Metric Design & Observing Behaviours6 分
Secondary Effects of Optimization4 分
Regulatory Concerns3 分
Weekly Summary2 分
6の練習問題
AI4Good Review5 分
Feedback Loops Review5 分
Metric Design Review5 分
Secondary effects Review5 分
Regulatory Concerns Review5 分
Responsible Machine Learning Review30 分
3

3

2時間で修了

Machine Learning in Production & Planning

2時間で修了
8件のビデオ (合計33分)
8件のビデオ
Users Break Things3 分
Time & Space complexity in production5 分
When do I retrain the model?4 分
Logging ML Model Versioning4 分
Knowledge Transfer4 分
Reporting Performance to Stakeholders4 分
Weekly Summary2 分
7の練習問題
Integrating Info Systems Review5 分
Complexity in Production Review5 分
Retrain the Model Review5 分
ML Versioning Review5 分
Knowledge Transfer Review5 分
Reporting to Stakeholders Review5 分
Machine Learning in Production and Planning Review30 分
4

4

5時間で修了

Care and Feeding of your Machine Learning System

5時間で修了
9件のビデオ (合計45分)
9件のビデオ
Post Deployment Challenges6 分
QuAM Monitoring and Logging5 分
QuAM Testing5 分
QuAM Maintenance3 分
QuAM Updating5 分
Separating Datastack from Production3 分
Dashboard Essentials & Metrics Monitoring5 分
Weekly Summary1 分
7の練習問題
Post Deployment Challenges Review5 分
Monitoring & Logging Review5 分
Testing Review5 分
Maintenance Review5 分
Updating Review5 分
Separating Datastack from Production Review5 分
Dashboard Monitoring Review5 分

レビュー

OPTIMIZING MACHINE LEARNING PERFORMANCE からの人気レビュー

すべてのレビューを見る

Machine Learning: Algorithms in the Real World専門講座について

This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results, and deploy it in the real world. You will also be able to anticipate and mitigate common pitfalls in applied machine learning....
Machine Learning: Algorithms in the Real World

よくある質問

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。