Today we take the first step towards the Google IT Automation with Python Professional Certificate. A program aimed at IT professionals, developed by Google, designed to equip them with in-demand skills including Python, Git, and other automation tools relevant to IT administration and management. It’s an excellent starting point for anyone looking to advance their IT career. This certificate can open doors to a variety of rewarding job roles. From data scientists and machine learning engineers to web developers and IT managers – the possibilities are endless.
As stated in my previous post, I am following the Coursera program, Google IT Automation with Python, to help me earn the certificate and get it on my resume ASAP. I’ll be reviewing, summarizing, and elaborating on the lessons, hopefully building a study guide for others to follow as supplemental material if they also wish to take the course, or try to earn the certification from my series alone.
This article will cover section 1 of the first week, which primarily covers high-level definitions of programming, automation, and it’s various benefits and limitations.
What is programming and scripting?
A script and a program are both sets of instructions that are executed by a computer. However, they differ in how they are processed and used.
- Processing: The main difference between a script and a program is that a script is interpreted, while a program is compiled. Scripts are read and executed line by line at runtime by an interpreter, software that directly executes computer instructions. Whereas a program is first translated into machine code by software known as a compiler before it’s run. This makes scripts easier to modify as you don’t need to recompile them after making changes. However, programs tend to run faster when they are directly executed by the computer’s hardware, as in the case of compiled code.
- Usage: Scripts are often used for automating tasks and manipulating data. They’re commonly used in web development to add interactive features to websites. Programs, on the other hand, are used to create standalone software applications.
- Complexity: Generally, scripting languages are less complex and easier to learn than programming languages. They usually require fewer lines of code to accomplish the same task as a programming language. They often accomplish this by importing libraries which contain a lot of premade functions that programmers don’t have to write out themselves.
- Examples: Python, JavaScript, and Ruby are examples of scripting languages, while C++, Java, and Rust are examples of programming languages.
Also note: All scripting languages are programming languages, but not all programming languages are used for scripting.
The Power of Automation
As you may already know, automation is the process of replacing manual steps with automatic ones. It’s a buzzword in today’s tech-driven world and for good reason. But like any other tool, knowing how to use it effectively is crucial.
In its simplest form, automation is replacing manual, repetitive steps with ones that occur automatically. It’s like setting your coffee maker to brew a fresh pot every morning at 7 AM, so you wake up to the aroma of java without lifting a finger.
For instance, imagine you own an e-commerce store. You receive hundreds of orders every day. Manually updating the inventory for each order is not only time-consuming but also prone to errors. Here, automation can be a lifesaver. With an automated system, the inventory updates itself every time an order is placed.
Let’s take traffic lights as another example. Could you imagine if we needed a person to manually control each intersection’s signals? The room for error would be enormous, and the task itself would be incredibly tedious. But with automation, traffic lights work seamlessly, reducing accidents and improving traffic flow.
Automation also increases consistency. When a task is performed manually, there’s always the risk of variability in the outcome due to human error or fatigue. However, an automated system will perform the same task with the same level of accuracy every time.
The Flip Side of Automation
However, it’s essential to understand that not all tasks are suited for automation. Tasks that require creativity, flexibility, or a human touch should not be automated.
While automation is powerful, it has its limits. Tasks that require human creativity, social interaction, complex analysis, or flexibility aren’t ideal for full automation. While you could automate the process of sifting through resumes for specific keywords, you’d still need a human to conduct the interview and assess the candidate’s fit for the company culture.
As another example, you can automate email responses to frequently asked questions, but you can’t automate a heartfelt response to a customer’s unique problem. In such scenarios, a human touch is irreplaceable. Although AI is increasingly encroaching on this area, many of us with experience using AI have seen the limitations that are still holding it back from unsupervised work.
Striking the Right Balance
So, how do you decide when to automate and when not to? This is where experience comes into play. Over time, as you work with different tasks and processes, you’ll develop an instinct for what should be automated and what shouldn’t.
Remember, automation is a tool. Like any other tool, it should be used wisely. Automate to improve efficiency, but don’t let it replace the human touch where it’s needed.
Mastering automation is not just about understanding the technology behind it. It’s also about knowing when and where to use it. Keep practicing, and soon, knowing when and where to use automation will become second nature to you.
Automation vs. AI
It’s also important to distinguish between basic automation and artificial intelligence (AI). Automation follows explicit instructions to perform a task, while AI involves training a machine to carry out more complex tasks through machine learning. This allows AI to handle new tasks without requiring explicit programming for each one.
For example, consider email spam filters. A basic automation might involve filtering out emails from specific addresses or with certain phrases. However, AI takes this a step further by learning from users’ actions (such as marking an email as spam) to better predict and filter future spam emails.
Automation in IT Administration
We spend our days using computers to perform a myriad of tasks. From creating user accounts, configuring networks, installing software, to backing up data – the list is endless. And in this sea of tasks, we often find ourselves performing the same actions repeatedly. That’s where automation comes into play.
Imagine you have gathered a massive list of emails from a conference. Now, you want to send them your monthly newsletter. But there’s a catch – some of them are already subscribed. How do you ensure everyone gets the newsletter without duplicating emails?
You could check each email manually, but that’s a recipe for boredom and errors. Instead, you could write a program that checks for duplicates and adds only new emails to the list. Your computer won’t get tired or make mistakes. And once the program is written, you can use it for similar tasks in the future.
Now, let’s take it a step further. When sending out these emails, you could automate the process to personalize each email with the recipient’s name and company. This results in more effective communication without spending hours manually inserting names into the text.
In essence, automating tasks allows us to focus on projects that require our creativity and problem-solving skills. It lets the computer handle the mundane, repetitive tasks.
Learning to Automate with Python
Learning to program is the first step towards harnessing the power of automation. And Python, with its simplicity and versatility, is an excellent language to start with.
One example of a powerful automated process might be a script that changes access permissions for numerous internal services. The script would traverse a large directory tree, checked file contents, and updated permissions based on specific conditions. A challenging task, but the sense of accomplishment can be extremely rewarding.
Week 1 Study Guide
At this point the course provides a study guide to prepare learners for the first Practice Quiz. Here are the key takeaways, much of which is a review of what was already discussed.
1. Programming Code
Think of programming code as a recipe that gives your computer step-by-step instructions on how to perform a task. Whether you’re asking your computer to calculate the square root of a number or automate an email response, it all starts with programming code. You might also hear it referred to as source code or scripts.
2. Programming Languages
Just like we communicate with each other using different languages, we use programming languages to communicate with computers. Some popular ones include Python, Java, C, C++, C#, and R. Each one has its unique syntax and semantics, just like spoken languages do.
3. Syntax and Semantics
Syntax is all about rules. In programming, syntax dictates how elements should be ordered and where special characters should be placed. It’s similar to the grammar rules we follow when we write or speak.
Semantics, on the other hand, is about meaning. Even if your code follows all the syntax rules, semantic (or logical) errors can still occur if the code doesn’t do what you intended it to do.
4. Computer Programs and Scripts
A computer program is a list of instructions that tells a computer to perform specific actions. These can range from simple tasks to complex operations.
Scripts, which are often shorter and less complex than full-fledged programs, are used to automate specific tasks. For example, a script could be written to automatically organize files in a directory.
5. Automation
Automation is the process of replacing a repetitive manual step with one that happens automatically. It’s like setting your coffee machine to brew a pot every morning at 7 a.m. so you don’t have to do it yourself.
6. Input and Output
Input is the information that a user provides to a program. This could be anything from text entered into a form to an image uploaded to a website.
Output is the end result of a program or function. This could be a calculated value, a report, entries into a database, and more.
7. Functions and Variables
Functions are reusable blocks of code that perform a specific task. They’re like little code machines that you can call upon whenever you need them to do their job.
Variables are the placeholders in your code. They store values that can change as your program runs, hence the name ‘variable’.
The Quiz
The first Quiz is a simple check if you paid attention and took notes on the information. All 5 questions are multiple choice, but later Quizzes will include coding problems where you will fill in blanks to solve for the presented problem or come to specified, desired result.
Week 1 Section 2 Preview
We’ve covered the basics, examined its strengths, identified its limitations, and even delved into the differences between basic automation and artificial intelligence. Next, we’ll get into the specifics of what Python is, and it’s key elements that we’ll need to understand. We’ll delve into its history, its unique characteristics, and why it’s so loved by beginners and pros alike.
There will also be some handy resources for learning Python, because while this course covers the fundamentals, there’s always more to discover. We’ll also learn about syntax and code blocks – two essential components of any programming language.
We’ll also learn why Python is relevant to IT work, as well as it’s relevance in data science, machine learning, and web development.
And for completeness the course will also discuss other languages that are worth learning for similar purposes. Each language has its own strengths and ideal use cases, and being familiar with a few can make you a more versatile IT professional.
Stay tuned, keep those notes handy, and remember – practice makes perfect!
