Harvard University · edX
Introduction to Data Science with Python
4.3174 ratingsLearn the concepts and techniques that make up the foundation of data science and machine learning.
Overview
This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required.
What you'll learn
- Differentiate between ML, AI and Deep Learning.
- Discuss the use of ML API’s on unstructured data.
- Execute BigQuery commands from Notebooks.
- Create ML models by using SQL syntax in BigQuery.
- Create ML models without coding using AutoML.
Syllabus 9
- In this module, we introduce the course and agenda.
- This module talks about ML options on Google Cloud.
- This module focuses on using pre-built ML APIs on your unstructured data.
- This module covers how to use Notebooks.
- This module covers building custom ML models and introduces Vertex AI and AI Hub.
- This module covers BigQuery ML.
- Custom model building with AutoML.
- This module recaps the topics covered in the course.
- PDF links to all modules.
Skills you'll practise
Advantages and disadvantages
Advantages
- University courses you can audit for free, with lectures, readings and practice quizzes.
- A verified certificate from the university if you pay for it.
- From Google, a well-regarded name.
- Self-paced: start any time.
- A clear syllabus (9 parts) you can see before you start.
Disadvantages
- Graded assignments and the certificate need the paid track.
- Audit access can expire a few weeks after the course ends.
- Learning is free, but the certificate costs money.
- Some parts (graded work, certificate) are paid.
Some points apply to every course of this kind; see how we rank.
Free to audit
- Free: Choose "Audit this course" when you enrol: lectures, readings and practice are free.
- Paid: Graded assignments and the verified certificate (Certificate $69). Audit access may end after the course closes.
Before you start
To benefit from this course, participants should have completed “Google Cloud Big Data and Machine Learning Fundamentals” or have equivalent experience.
Taught by
- Google Cloud TrainingCourse Team
Google is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (88/100). They build what they teach.
Similar courses
MIT 14.310x Data Analysis for Social Scientists, Spring 2023
Instructors: Esther Duflo and Sara Ellison View the complete course: https://ocw.mit.edu/courses/14-310x-data-analysis-for-social-scientists-spring-2023 This course introduces methods for harnessing data to answer questions of cultural, social, economic, and policy interest. We will start with esse…
Harvard University · edX
Data Science: R Basics
4.4273 ratingsBuild a foundation in R and learn how to wrangle, analyze, and visualize data.
MIT 15.071 The Analytics Edge, Spring 2017
View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Dimitris Bertsimas Students of this course learn how to use data and analytics by examining real world examples and utilizing methods including linear and logistic regression, trees, text analytics, clustering, visualization, and o…
Harvard University · edX
Data Science: Visualization
4.4122 ratingsLearn basic data visualization principles and how to apply them using ggplot2.
Harvard University · edX
Causal Diagrams: Draw Your Assumptions Before Your Conclusions
4.830 ratingsLearn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.