(Applied Data Science with Python の専門分野)

May 21 開始

(Applied Data Science with Python の専門分野)

Gain new insights into your data 。Learn to apply data science methods and techniques, and acquire analysis skills.

この専門講座について

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have basic a python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.

作成者:

courses
5 courses

提案の順序に従うか、ご自分で選択してください。

projects
プロジェクト

習得したスキルの実践および応用を目的として作成されています。

certificates
修了証

履歴書またはLinkedInで新しいスキルを強調します。

コース
Intermediate Specialization.
Some related experience required.
  1. コース 1

    Introduction to Data Science in Python

    現在のセッション:May 21
    字幕
    English, Korean, Vietnamese, Chinese (Traditional)

    コースについて

    This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will i
  2. コース 2

    Applied Plotting, Charting & Data Representation in Python

    今後のセッション:May 28
    字幕
    English

    コースについて

    This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good
  3. コース 3

    Applied Machine Learning in Python

    今後のセッション:Jun 4
    字幕
    English

    コースについて

    This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than des
  4. コース 4

    Applied Text Mining in Python

    今後のセッション:Jun 4
    字幕
    English

    コースについて

    This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk frame
  5. コース 5

    Applied Social Network Analysis in Python

    現在のセッション:May 21
    字幕
    English, Korean

    コースについて

    This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week in

作成者

  • ミシガン大学(University of Michigan)

    Michigan’s academic vigor offers excellence across disciplines and around the globe. The University is recognized as a leader in higher education due to the outstanding quality of its 19 schools and colleges, internationally recognized faculty, and departments with 250 degree programs.

    The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.

  • Christopher Brooks

    Christopher Brooks

  • Kevyn Collins-Thompson

    Kevyn Collins-Thompson

    Associate Professor
  • Daniel Romero

    Daniel Romero

    Assistant Professor
  • V. G. Vinod Vydiswaran

    V. G. Vinod Vydiswaran

    Assistant Professor

FAQs