Online Course – Certified Professional Specialization in Data Products for Python – Analytics and Predictions at Google and the University of California San Diego

Build predictive systems with precision. Collect, model, and deploy data-driven systems using Python and machine learning.

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קורס אונליין - התמחות מקצועית מוסמכת במוצרים נתוניים לפייתון - אנליטיקה ותחזיות בגוגל ובאוניברסיטת קליפורניה סן דייגו

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Predictive analytics
  • Python programming
  • Machine learning
  • Data processing
  • Data visualization

What you will learn in the course

Courses for which the course is suitable

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Machine learning model developer
  • Predictive Analytics Specialist
  • Data Project Manager
  • Technology consultant in the field of artificial intelligence
  • Software developer with a specialization in data

Internship – a four-part course series

Data-driven products in Python are driving the AI ​​revolution. Leading companies like Google, Facebook, and Netflix are using predictive analytics to improve the products and services we use every day. Upgrade your Python skills and learn to make accurate predictions with data-driven systems and implement machine learning models with this four-course specialization from the University of California, San Diego.

Internship goals

  • Learners who know the basics of Python.
  • Creating a data-first strategy.
  • Development of statistical models.
  • Creating data-driven workflows.
  • Learning to produce meaningful predictions for business and research purposes.
  • Using design thinking methods and data science techniques.

This is your chance to master one of the most sought-after skills in the tech industry.

Data Products Course in Python for Predictive Analytics

The course is taught by Professor Ilkay Altınç, PhD, and Julian McAuley. Dr. Altınç is a prominent figure in the data science community and the designer of the popular “Big Data” specialization on the Coursera platform. She has helped educate hundreds of thousands of learners on how to extract value from massive amounts of data.

Hands-on Learning Project
  • Creating a data-first strategy.
  • Development of statistical models.
  • Creating data-driven workflows.
  • Learning to produce meaningful predictions for business and research purposes.
  • Using design thinking methods and data science techniques.

This is your chance to master one of the most sought-after skills in the tech industry.

Details of the courses that make up the specialization

Base data, processing and visualization

Course 1

  • 10 hours
  • 4.3 (191 ratings)
Course Details
What will you learn?
  • Developing a data strategy and process for creating, collecting, and using data
  • Load and process formatted data sets like CSV and JSON.
  • Work with data in different formats (e.g., timestamps, strings) and filter and clean data sets by removing extreme values, etc.
  • Basic experience with data processing libraries like numpy and retrieving data with urllib, requests
Skills you will acquire
  • Category: Python libraries
  • Category: Data Preprocessing
  • Category: Data Visualization
  • Category: Data collection from the Internet

Design Thinking and Predictive Analytics for Data-Driven Products

Course 2

  • 8 hours
  • 4.5 (63 ratings)
Course Details
What will you learn?
  • This is the second course in a four-course training on predictive data products in Python, building on the data processing learned in Course 1 and introducing the fundamentals of designing predictive models in Python.
  • In this course, you will understand the basic concepts of statistical learning and learn different methods for building predictive models.
  • At each stage of the training, you will gain practical experience in data processing and developing your skills, and you will finish with a summary project that includes all the concepts learned in the training.

Significant predictive models

Course 3

  • 8 hours
  • 4.3 (48 ratings)
Course Details
What will you learn?
  • Understanding the definitions of simple error measures (e.g., MSE, precision, sensitivity/detection).
  • Evaluating the performance of regressors/classifiers using the above metrics.
  • Understanding the difference between training/testing performance and universality.
  • Understanding techniques to avoid overfitting and achieve good universality performance.

Implanting machine learning models

Course 4

  • 10 hours
  • 3.5 (51 ratings)
Course Details
What will you learn?
  • Project structure for interactive data applications in Python
  • Python web server frameworks: (e.g.) Flask, Django, Dash
  • Best practices for deploying machine learning models and tracking performance
  • Scripts for implementation, model ordering, APIs
Skills you will acquire
  • Category: Python Programming
  • Category: Big Data Products
  • Category: Recommendation Systems

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