IBMデータサイエンス プロフェッショナル認定証

• 返金ポリシーについて教えてください。

  サブスクライブすると、7日間の無料トライアルを体験できます。この期間中は解約金なしでキャンセルできます。それ以降、払い戻しはありませんが、サブスクリプションをいつでもキャンセルできます。返金ポリシーをすべて表示します。

• 1つのコースだけに登録することは可能ですか？

  はい。まず始めに興味のあるコースカードをクリックして登録します。コースに登録して修了することによって、共有できる修了証を取得するか、無料でコースを聴講してコースの教材を確認することができます。修了証の一部であるコースにサブスクライブすると、修了証全体に自動的にサブスクライブされます。進捗を追跡するには、受講生のダッシュボードにアクセスしてください。

• このコースは100%オンラインで提供されますか？実際に出席する必要のあるクラスはありますか？

  このコースは完全にオンラインで提供されているため、実際に教室に出席する必要はありません。Webまたはモバイル機器からいつでもどこからでも講義、学習用教材、課題にアクセスできます。

• How can I earn my IBM Badge?

  Upon completion of this program, you will receive an email from Coursera with directions on how to claim your IBM Badge through Acclaim. Learn more about IBM Badges 

• What is data science?

  D​ata science is the process of collecting, storing, and analyzing data. Data scientists use data to tell compelling stories to inform business decisions. Learn more about what data science is and what data scientists do in the first course of this Professional Certificate, "What is Data Science?"

• What are some examples of careers in data science?

  An understanding of data science and the ability to make data driven decisions is useful in any career, but some careers specifically require a data science background. Some examples of careers in data science include: 

  -​ Business Intelligence Analyst

  -​ Data Analyst

  -​ Data Architect

  -​ Data Engineer

  -​ Data Scientist

  -​ Machine Learning Engineer

  -​ Marketing Analyst

  -​ Operations Analyst

  -​ Quantitative Analyst

• How long does it take to complete the Professional Certificate?

  The Professional Certificate requires completion of 9 courses. Each course typically contains 3-6 modules with an average effort of 2 to 4 hours per module. If learning part-time (e.g. 1 module per week), it would take 6 to 12 months to complete the entire certificate. If learning full-time (e.g. 1 module per day) the certificate can be completed in 2 to 3 months.

• What background knowledge do I need for this program?

  This Professional Certificate is open for anyone with any job and academic background. No prior computer programming experience is necessary, but is an asset, as are familiarity working with computers, high school math, and communication and presentation skills. For the last few courses, knowledge of calculus and linear algebra is an asset but not an absolute requirement.

• Do I need to take the courses in a specific order?

  Yes, it is highly recommended to take the courses in the order they are listed, as they progressively build on concepts taught in previous courses. For example the Data Analysis, Data Visualization, and Machine Learning courses require knowledge of Python covered earlier in the program.

• What will I be able to do upon completing the Professional Certificate?

  Become job ready for a career in Data Science. Develop practical skills using hands-on labs in Cloud environments, projects and captsones.

• I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?

  If you have already completed some of the courses in this Professional Certificate, either individually or as part of another Specialization, they will be marked as "Complete". You do not have to take those courses again, and will be able to finish the Professional Certificate more quickly. You will only need to complete the courses that you have not yet completed.

• I have already completed the Introduction to Data Science Specialization. Can I still enroll in this Professional Certificate?

  Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". You do not have to take those courses again and will be able to finish the Professional Certificate more quickly.

• Which program should I enroll in - the Introduction to Data Science Specialization, or this Professional Certificate?

  This Professional Certificate consists of 9 courses. The "Introduction to Data Science" Specialization has 4 courses, all of which are also included in this Professional Certificate.

  If you are unsure about your ability to commit to the level of effort and time required to complete this Professional Certificate, we recommend starting with the Introduction to Data Science Specialization, which has fewer courses. If, after completing the Specialization, you are still determined to continue building your data science skills, you can then enroll for this Professional Certificate and then just complete the courses that are not in the Specialization.

• I have already completed the Applied Data Science Specialization. Can I still enroll in this Professional Certificate?

  Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". You do not have to take those courses again and will be able to finish this Professional Certificate more quickly.

• How can I access job opportunities with IBM and other organizations after completing this Professional Certificate?

  As a Coursera learner who completes this Professional Certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.

• Can I get college credit for taking the IBM Data Science Professional Certificate ?

  Yes. The IBM Data Science Professional Certificate recently secured a credit recommendation from the American Council on Education's (ACE) Credit Recommendation, which is the industry standard for translating workplace learning to college credit. Learners can earn a recommendation of 12 college credits for completing the program. This aims to help open up additional pathways to learners who are interested in higher education and prepare them for entry-level jobs.

• How do you share your proof of completion with the educational institutions for transferring credit?

  To share proof of completion with schools, certificate graduates will receive an email prompting them to claim their Credlybadge, which contains the ACE®️credit recommendation.  Once claimed, you will receive a competency-based transcript that signifies the credit recommendation, which can be shared directly with a school from the Credly platform. Please note that the decision to accept specific credit recommendations is up to each institution and is not guaranteed. 

• Where can I find more information on ACE credit recommendations?

  Please see Coursera’s ACE Recommendations FAQ.

さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。