In this post, you will quickly learn about key learning from free course on Technical writing by Google.
- Define new or unfamiliar terms: When writing or editing, learn to recognize terms that might be unfamiliar to some or all of your target audience. If the term already exists, link to a good existing explanation. In case your document is introducing the term, define the term properly.
- Use acronyms properly: On the initial use of an unfamiliar acronym within a document or a section, spell out the full term, and then put the acronym in parentheses.
- Active voice vs Passive voice: Prefer active voice to the passive voice
- Clear Sentences
- Choose strong verbs
- Avoid there is/there are
- Short Sentences
- Focus each sentence on a single idea
- Convert some long sentences to lists
- Eliminate unneeded words
- Reduce subordinate clauses; Follow the one-sentence = one idea in the mind. Do the subordinate clauses in a sentence extend the single idea or do they branch off into a separate idea? If the latter, consider dividing the offending subordinate clause(s) into separate sentences.
- List and tables
- Choose the correct type of list
- Bulleted lists (Unordered items)
- Numbered lists (Ordered items): Start the numbered list items with imperative words
- Embedded lists: An embedded list (sometimes called a run-in list) contains items stuffed within a sentence
- Choose the correct type of list
- Paragraphs
- Write a great opening sentence
- Focus each paragraph on a single topic
- Answer what, why, and how
- Don’t make paragraphs too long or too short
- Audience
- Define your audience
- Determine what your audience needs to learn.
- Documents
- State your document’s scope
- State your audience
- Establish your key points up front
- Break your topics into sections
- Define your audience
- Illustrating
- Write the caption first
- Constrain the amount of information in a single drawing
- Focus the reader’s attention
- Creating sample code
- Provide code samples which are correct and concise code that your readers can quickly understand and easily reuse with minimal side effects.
Latest posts by Ajitesh Kumar (see all)
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024
- Anxiety Disorder Detection & Machine Learning Techniques - October 4, 2024
- Confounder Features & Machine Learning Models: Examples - October 2, 2024
I found it very helpful. However the differences are not too understandable for me