Golang: Logic Flow and Data Collections

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Golang: Logic Flow and Data Collections

Coursera · Beginner ·📐 ML Fundamentals ·2w ago

Key Takeaways

Covers logic flow and data collections in Golang programming language

Original Description

Go (Golang) programs don't just store data — they make decisions, repeat actions, and organize information efficiently. Golang: Logic Flow & Data Collections is where your Go skills move from syntax to real programming power. Designed for developers who understand basic syntax and want to master data manipulation and program logic in Go, this course covers the three layers that control how Go programs think and handle data. You'll start with Go's full operator toolkit — arithmetic, logical, assignment, and bitwise operators — learning how to evaluate complex conditions and manipulate data at the bit level. From there, you'll build decision-making logic using if-else branching and switch statements, then add iteration using Go's versatile for loop. The course closes with Go's three core data collection types: Arrays, Slices, and Maps. You'll understand how each one works internally, when to use each, and how to iterate through and manipulate data sets with professional efficiency. Special emphasis is placed on Slices — including their underlying relationship with Arrays — a topic that defines expert-level Go development. Every module pairs video lessons with hands-on coding labs, practice quizzes, and AI-guided role-plays — including building a Smart Access Controller and an Inventory Audit Script — to put your logic and data skills to work in realistic backend scenarios. This course is essential for anyone building data-driven tools or backend services. By completion, you will have the skills to handle collections of data with professional-level efficiency.
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
ML/DL Engineer looking for open-source repos to contribute to (Pytorch experience) [P]
Contribute to open-source ML projects with PyTorch experience to work on real-world problems and learn from strong engineers
Reddit r/MachineLearning
📰
One validation set, or two? Testing an old habit on 89 datasets
Learn when to use one or two validation sets for early stopping in machine learning and why it matters for model performance
Medium · Machine Learning
📰
The extra validation set is useless: cross-validation can pick both your model and your number of…
Learn why a separate validation set may not be necessary for early stopping and how cross-validation can be used instead
Medium · Data Science
📰
GetWhitefox
Learn about WhiteFox, a machine learning platform, and its capabilities
Medium · Machine Learning
Up next
SQLite3 Tutorial - Learn SQL for Python in 17 Minutes
Thomas Janssen
Watch →