Über diesen Kurs

37,641 kürzliche Aufrufe
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100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
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Stufe „Mittel“

B​asic knowledge of programming (any language)

Ca. 10 Stunden zum Abschließen
Englisch
Untertitel: Englisch

Was Sie lernen werden

  • Develop data strategy and process for how data will be generated, collected, and consumed

  • Load and process formatted datasets such as CSV and JSON.

  • Deal with data in various formats (e.g. timestamps, strings) and filter and “clean” datasets by removing outliers etc.

  • Basic experience with data processing libraries such as numpy and data ingestion with urllib, requests

Kompetenzen, die Sie erwerben

Python LibrariesData Pre-ProcessingData Visualization (DataViz)Web Scraping
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“

B​asic knowledge of programming (any language)

Ca. 10 Stunden zum Abschließen
Englisch
Untertitel: Englisch

von

University of California San Diego-Logo

University of California San Diego

Lehrplan - Was Sie in diesem Kurs lernen werden

Woche
1

Woche 1

2 Stunden zum Abschließen

Week 1: Introduction to Data Products

2 Stunden zum Abschließen
6 Videos (Gesamt 42 min), 6 Lektüren, 2 Quiz
6 Videos
Data Product Examples in Enterprise5m
Developing a Data Product Strategy7m
Python and Jupyter Basics6m
Python Recap5m
Livecoding: Getting Started With Jupyter10m
6 Lektüren
Syllabus10m
Course Materials10m
Set Up Your System10m
Our Case Study: Recommender Systems10m
(Optional) Python: How to Run10m
(Optional) Python: Additional Resources and Recommended Readings10m
2 praktische Übungen
Review: Data Products4m
Review: Python and Jupyter5m
Woche
2

Woche 2

2 Stunden zum Abschließen

Week 2: Reading Data in Python

2 Stunden zum Abschließen
6 Videos (Gesamt 54 min)
6 Videos
Reading CSV & JSON Files9m
Processing Structured Data in Python8m
Live-Coding: JSON5m
Extracting Simple Statistics From Datasets11m
Simple Statistics: Live-Coding8m
3 praktische Übungen
Review: CSV and JSON Files8m
Review: Simple Statistics10m
Python: Reading Data and Simple Statistics45m
Woche
3

Woche 3

1 Stunde zum Abschließen

Week 3: Data Processing in Python

1 Stunde zum Abschließen
4 Videos (Gesamt 38 min)
4 Videos
Processing Text and Strings in Python7m
Processing Times and Dates in Python11m
Livecoding: Time and Date Data8m
3 praktische Übungen
Review: Data Filtering and Cleaning5m
Review: Processing Different Data Types5m
Data Processing in Python30m
Woche
4

Woche 4

2 Stunden zum Abschließen

Week 4: Python Libraries and Toolkits

2 Stunden zum Abschließen
5 Videos (Gesamt 45 min)
5 Videos
Introduction to Data Visualization11m
Introduction to Matplotlib5m
Live-coding: MatPlotLib9m
urllib and BeautifulSoup12m
4 praktische Übungen
Review: NumPy4m
Review: MatPlotLib6m
Review: urllib and BeautifulSoup6m
Python Libraries and Toolkits15m

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Über den Spezialisierung Python Data Products for Predictive Analytics

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego. This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets....
Python Data Products for Predictive Analytics

Häufig gestellte Fragen

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • 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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • 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, 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.

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