Introduction to Data Science in Python

Цена: Бесплатный

День проведения: По запросу

Тип: Электронное обучение

Категория: Анализ данных

Язык: Английский

Местонахождение: Онлайн

Описание тренинга:

 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 introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.

Кто может принять участие:

 This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. The class is taught in a tutorial format using the pandas library, and only a minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.

Дополнительная информация

WEEK 1

Week 1

In this week you'll get an introduction to the field of data science, review common Python functionality and features which data scientists use, and be introduced to the Coursera Jupyter Notebook for the lectures. All of the course information on grading, prerequisites, and expectations are on the course syllabus, and you can find more information about the Jupyter Notebooks on our Course Resources page.

 

WEEK 2

Week 2

In this week of the course you'll learn the fundamentals of one of the most important toolkits Python has for data cleaning and processing -- pandas. You'll learn how to read in data into DataFrame structures, how to query these structures, and the details about such structures are indexed. The module ends with a programming assignment and a discussion question.

 

WEEK 3

Week 3

In this week you'll deepen your understanding of the python pandas library by learning how to merge DataFrames, generate summary tables, group data into logical pieces, and manipulate dates. We'll also refresh your understanding of scales of data, and discuss issues with creating metrics for analysis. The week ends with a more significant programming assignment.

 

WEEK 4

Week 4

In this week of the course you'll be introduced to a variety of statistical techniques such a distributions, sampling and t-tests. The majority of the week will be dedicated to your course project, where you'll engage in a real-world data cleaning activity and provide evidence for (or against!) a given hypothesis. This project is suitable for a data science portfolio, and will test your knowledge of cleaning, merging, manipulating, and test for significance in data. The week ends with two discussions of science and the rise of the fourth paradigm -- data driven discovery.

 

Coursework

Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers

Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

 

7-day Free Trial

Introduction to Data Science in Python is part of the larger Applied Data Science with Python Specialization. Your 7-day free trial includes:

  • Unlimited access to all courses in the Specialization

    Watch lectures, try assignments, participate in discussion forums, and more.

  • Cancel anytime.

    No penalties - simply cancel before the trial ends if it's not right for you.

  • $49 USD per month to continue learning after trial ends.

    Go as fast as you can - the faster you go, the more you save.

  • Certificate when you complete.

    Share on your resume, LinkedIn, and CV.

Выступающие:

Christopher Brooks

Taught by:  Christopher Brooks

Участие

Крайний срок регистрации 16 Ноябрь 2019

To participate in this training, you can Enroll

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Информация об учебном центре

Тип компании: Другое

Количество сотрудников: 500-1500

О компании:

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