- Data Science
- Artificial Intelligence (AI)
- Machine Learning
- Predictive Analytics
- Ethics Of Artificial Intelligence
- Machine learning strategy and leadership
- Machine Learning (ML) Algorithms
Machine Learning Rock Star – the End-to-End Practice 專項課程
An End-to-End Guide to Leading and Launching ML. This expansive machine learning curriculum is accessible to business-level learners and yet vital to techies as well. It covers both the state-of-the-art techniques and the business-side best practices.
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您將學到的內容有
Lead ML: Manage or participate in the end-to-end implementation of machine learning
Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more
Greenlight ML: Forecast the effectiveness of and scope the requirements for a machine learning project and then internally sell it to gain buy-in
Regulate ML: Manage ethical pitfalls, the risks to social justice that stem from machine learning – aka AI ethics
您將獲得的技能
關於此 專項課程
應用的學習項目
Problem-solving challenges: Form an elevator pitch, build a predictive model by hand in Excel or Google Sheets to visualize how it improves, and more (no exercises involve the use of ML software).
Vendor-Neutral
This specialization includes several illuminating software demos of ML in action using SAS products. However, the curriculum is vendor-neutral and universally-applicable. The learnings apply, regardless of which ML software you end up choosing to work with.
In-Depth Yet Accessible
Brought to you by a veteran industry leader who won teaching awards when he was a professor at Columbia University, this specialization stands out as one of the most thorough, engaging, and surprisingly accessible on the subject of ML.
Like a University Course
These three courses are also a good fit for college students, or for those planning for or currently enrolled in an MBA program. The breadth and depth of this specialization is equivalent to one full-semester MBA or graduate-level course.
Accessible to business-side learners yet also vital to techies. Engage in the commercial use of ML – whether you're an enterprise leader or a quant.
Accessible to business-side learners yet also vital to techies. Engage in the commercial use of ML – whether you're an enterprise leader or a quant.
專項課程的運作方式
加入課程
Coursera 專項課程是幫助您掌握一門技能的一系列課程。若要開始學習,請直接註冊專項課程,或預覽專項課程並選擇您要首先開始學習的課程。當您訂閱專項課程的部分課程時,您將自動訂閱整個專項課程。您可以只完成一門課程,您可以隨時暫停學習或結束訂閱。訪問您的學生面板,跟踪您的課程註冊情況和進度。
實踐項目
每個專項課程都包括實踐項目。您需要成功完成這個(些)項目才能完成專項課程並獲得證書。如果專項課程中包括單獨的實踐項目課程,則需要在開始之前完成其他所有課程。
獲得證書
在結束每門課程並完成實踐項目之後,您會獲得一個證書,您可以向您的潛在雇主展示該證書並在您的職業社交網絡中分享。

此專項課程包含 3 門課程
The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
It's the age of machine learning. Companies are seizing upon the power of this technology to combat risk, boost sales, cut costs, block fraud, streamline manufacturing, conquer spam, toughen crime fighting, and win elections.
Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership
Machine learning runs the world. It generates predictions for each individual customer, employee, voter, and suspect, and these predictions drive millions of business decisions more effectively, determining whom to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate.
Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls
Machine learning. Your team needs it, your boss demands it, and your career loves it. After all, LinkedIn places it as one of the top few "Skills Companies Need Most" and as the very top emerging job in the U.S.
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SAS
Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. SAS is a trusted analytics powerhouse for organizations seeking immediate value from their data. A deep bench of analytics solutions and broad industry knowledge keep our customers coming back and feeling confident. With SAS®, you can discover insights from your data and make sense of it all. Identify what’s working and fix what isn’t. Make more intelligent decisions. And drive relevant change.
常見問題
退款政策是如何规定的?
我可以只注册一门课程吗?
有助学金吗?
我可以免费学习课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程后我会获得大学学分吗?
Is this specialization for data scientists or is it for non-technical, business-level learners?
How technical is this specialization and how much math is involved?
Are the learnings specific to SAS software?
Is this specialization for industry professionals or for university students?
Do I need to take the courses in a specific order?
AI ethics: Is equitable machine learning possible or will predictive models always perpetuate social injustice?
還有其他問題嗎?請訪問 學生幫助中心。