Harvard University · edX
Fundamentals of TinyML
4.567 ratingsFocusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
Overview
Unlock the power of Git with this hands-on course that will teach you how to work with and manage code in the context of current software development.
Whether you’re a developer, system administrator, or casual Git user, this course is the place to start with utilizing advanced Git within GitLab or Bitbucket to enable more reliable collaboration and robust source code management.
You'll learn how to improve your workflow by leveraging the power of Git's version control, as well as the collaboration features of GitLab and Bitbucket, through hands-on activities.
By the end of this course, you will be familiar with Git commands, branching, merging, and conflict resolution, as well as how to use GitLab and Bitbucket for seamless integration and project management. You will be able to easily manage repositories, collaborate on code, and keep track of project history.
This course is ideal for developers, IT professionals, and anyone seeking to refine their Git skills for effective team collaboration. Enroll now to improve your growth processes; your future self will thank you!
Syllabus 3
- Working with GitLab 1 hour
This module introduces GitLab and its core concepts including account setup and remote repository management. It also covers push/pull operations and working with merge requests using practical demos.
- Working with Bitbucket 40 minutes
This module explains Bitbucket concepts, account creation, and repository management workflows. It also includes forking, cloning, and performing push/pull operations in Bitbucket.
- Bitbucket Collaboration & Workflows 40 minutes
This module focuses on working with merge requests, resolving branch conflicts, and handling advanced collaboration workflows. It also demonstrates end-to-end GitLab and Bitbucket integration in real-world scenarios.
Advantages and disadvantages
Advantages
- Structured courses with graded quizzes, assignments and deadlines you can reset.
- A shareable certificate from the university or company when you pay.
- Financial aid is often approved for students in India (apply 15 days before you need it).
- Covers niche tools that universities don't teach.
- Self-paced: start any time.
- A clear syllabus (3 parts) you can see before you start.
Disadvantages
- Paid after a 7-day free trial (Coursera Plus or per course).
- Some courses can be audited for free, but graded work and certificates need payment.
- Many courses are produced quickly from slides and screen recordings; read the reviews first.
Some points apply to every course of this kind; see how we rank.
This course is paid. Here is how to take it for free
- Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
- Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.
Taught by
- LearnKartS
LearnKartS is in Tier 5: mass-produced or unclear of our institution ranking (40/100).
Similar courses
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.
Harvard University · edX
CS50's Introduction to Computer Science
An introduction to the intellectual enterprises of computer science and the art of programming.
Harvard University · edX
Data Science: Building Machine Learning Models
4.4133 ratingsBuild a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.
Harvard University · edX
CS50's Introduction to Programming with Python
An introduction to programming using Python, a popular language for general-purpose programming, data science, web programming, and more.
Harvard University · edX
Data Science: R Basics
4.4273 ratingsBuild a foundation in R and learn how to wrangle, analyze, and visualize data.