この専門講座について

25,325 最近の表示

Do you find yourself in an industry or field that increasingly uses data to answer questions? Are you working with an overwhelming amount of data and need to make sense of it? Do you want to avoid becoming a full-time software developer or statistician to do meaningful tasks with your data?

Completing this specialization will give you the skills and confidence you need to achieve practical results in Data Science quickly. Being able to visualize, analyze, and model data are some of the most in-demand career skills from fields ranging from healthcare, to the auto industry, to tech startups.

This specialization assumes you have domain expertise in a technical field and some exposure to computational tools, such as spreadsheets. To be successful in completing the courses, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation).

Throughout this specialization, you will be using MATLAB. MATLAB is the go-to choice for millions of people working in engineering and science, and provides the capabilities you need to accomplish your data science tasks. You will be provided with free access to MATLAB for the duration of the specialization to complete your work.

共有できる証明書
修了時に証明書を取得
100%オンラインコース
自分のスケジュールですぐに学習を始めてください。
フレキシブルなスケジュール
柔軟性のある期限の設定および維持
初級レベル
約3か月で修了
推奨4時間/週
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%オンラインコース
自分のスケジュールですぐに学習を始めてください。
フレキシブルなスケジュール
柔軟性のある期限の設定および維持
初級レベル
約3か月で修了
推奨4時間/週
英語
字幕:英語

この専門講座には4コースあります。

コース1

コース 1

Exploratory Data Analysis with MATLAB

4.8
338件の評価
94件のレビュー
コース2

コース 2

Data Processing and Feature Engineering with MATLAB

4.7
130件の評価
42件のレビュー
コース3

コース 3

Predictive Modeling and Machine Learning with MATLAB

コース4

コース 4

Data Science Project: MATLAB for the Real World

提供:

MathWorks ロゴ

MathWorks

よくある質問

  • 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! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • 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.

  • 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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Basic math, statistics and some experience working with spreadsheets will be helpful. No prior experience with MATLAB or programming is necessary.

  • Yes. A free license is available to learners enrolled in the course. You must have a computer capable of running MATLAB. You can view the system requirements here.

  • You will be able to:

    • Import data from a variety of sources into MATLAB

    • Create compelling visualizations

    • Analyze and calculate statistics on groups of data

    • Perform common data cleaning techniques

    • Identify and create new features for machine learning models

    • Apply common machine learning methods and evaluate their performance

  • It is recommended that you take the courses in order. The skills gained in course one is considered pre-requiste knowledge for course two.

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。