Ange Canlas Balandra

Academy Xi Blog

Student Spotlight: Ange Canlas Balandra

By Academy Xi

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Ange Canlas Balandra

Keen to hone her coding skills but also looking to balance learning with the rest of life, Ange enrolled in the Software Engineering: Transform course.  

From building web games on the school computers, to developing full-stack web apps, Ange has come a long way with Software Engineering. Find out how studying with Academy Xi is helping Ange transition into a career she’s seriously passionate about.

Why don’t you start by telling us about your career history?

When I finished high school I went to a local college. I started by completing a certificate in telecoms and then after that, took a certificate in assistant nursing. At that stage in my life, I really didn’t know what I wanted to do in terms of a career. 

My family pushed me to go to university, so I ended up studying a bachelor’s degree in nursing, but I was never really sure about the course myself. I decided I wanted to do something I was passionate about. I’d always loved coding, so I decided to quit the nursing degree and take the Academy Xi course in Software Engineering. 

What appealed to you about Software Engineering?

I started coding when I was about 16 or 17. I used the school computers to program basic web app games. When I made the decision to follow my heart in my career, taking a bootcamp coding course was the obvious path to follow.

There’s definitely a bit of a stigma about Software Engineers, with lots of people believing that coding is a man’s profession. I felt like I had a chance to prove that stigma wrong. I wanted to complete the Academy Xi course and earn a formal certification, which would prove that I really can code to a high level.  

Why did you choose Academy Xi?

I looked at a few different courses in Sydney, but in the end decided I wanted something that allowed me to study online. 

I studied my nursing degree on campus. Lots of what we were learning was practical and had to be taught in-person. It meant I didn’t really have enough time to look after myself and as well as to be able to juggle getting to work and such, which is also really important. I picked Academy Xi because it seemed to be the most flexible option and would fit nicely around my work, study and lifestyle schedule.

Did you enjoy the course?

I absolutely loved it! Honestly, there were a few moments when I felt like dropping out. I had deadlines and things became a bit overwhelming. Instead, I put the extra time in and worked really hard on the assessments. I wanted to finish all the projects so I could showcase them in my portfolio. 

In the end, I managed to find the determination to hang in there when things got tough. I’m so glad I did, because it was a huge satisfaction to complete the course. 

How did you find working with your mentor? 

My mentor was Frae Valdehuesa – he’s full of knowledge and a nice person. He gave me a lot of encouragement and congratulated me when I completed my assessments. 

I had unlimited 1:1 sessions with Frae and I’d get loads of practical advice from him. Every time I had an assessment, I’d be able to book a session with Frae and we’d review the project together. Sometimes my coding practice would be incorrect and Frea would explain why. As well as the free resources, I relied on those sessions to guide me through the course. 

What would you pick as your highlight for the course?

I’d have to say completing all the projects. They gradually increased in complexity, which was a great way to build on my coding skills. 

The first project used HTML and CSS, the second was with Javascript, the third involved combining HTML, CSS and Javascript, and the fourth was full-stack, usingRails and Redux

The fourth project was definitely the most challenging, but also the most rewarding. I created a video game database, using Rails for the server-side coding,  Redux, JS and JSX for the front-end, and then CSS to style everything. The end product brought together all the coding languages and technical skills I’d developed throughout the course.

What are your plans for the future? 

I’m working through the career toolkit that the Academy Xi Career Support Program provides, which is helping me polish up my resume and cover letter. I’ve also got all my projects presented and narrated in Github, so I’ve got a portfolio that I’m really pleased with. 

Before the course started, I was contemplating also doing a degree in Software Engineering, but the fees are really high and I don’t want to take on such a big loan. I know that most people go from Academy Xi Transform courses straight into industry, so why not me? I’m going to continue working with the Career Support Program and start applying for jobs – hopefully I can land a programming role soon. 

Would you recommend Academy Xi? 

Speaking from my experience with the Software Engineering course, definitely. The course was challenging and a challenge is always a good thing. My mentor was friendly, helpful and supportive. If you want to pick up full-stack coding skills in a short space of time, I’d say go for it. 

 Want to become a full-stack developer and learn the works of front-end and back-end web development just like Ange? Checkout our Software Engineering: Transform course. 

chatbot chatGPT

Academy Xi Blog

The world’s most advanced AI chatbot: ChatGPT

By Academy Xi

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chatbot chatGPT

An OpenAI bot called ChatGPT is causing a stir online after more than one million users signed up in the first few days of its release. Read on to find out what ChatGPT is, how it works, and what it means for the future of tech and employment.  

Let’s face it, we’ve all dropped the ball at some point. You open up your Google calendar expecting to find a breezy Friday morning ahead of you, but realise you’ve got an important meeting in less than half an hour. 

You’re meant to be presenting an updated company value proposition to the board and you haven’t even started it. In the past, you’d say you need a miracle. These days, all you need is ChatGBT. Freakout averted.

What’s ChatGPT?

ChatGPT is a prototype AI chatbot that’s capable of understanding human language and generating impressively human-like written text. It’s the latest evolution of the GPT – short for Generative Pre-Trained Transformer – a family of AI that specialises in generating written text.

what is chatGBT

To give an example, if you log into ChatGPT and input a command of “write a company value proposition for Academy Xi”, ChatGPT will rattle off a written response in about 20 seconds. It will be grammatically flawless and astoundingly detailed. 

The possibilities are limitless. You can use ChatGPT to whip up a snappy bio for your LinkedIn page, write a corporate white paper, pen the script for a movie, or even compose a degree-level essay. In short, ChatGPT gives you whatever written content you need, whenever you need it. 

Beyond taking the heavy lifting out of writing, ChatGPT has a vast array of applications, including: 

  • Solving mathematical equations
  • Debugging and fixing code
  • Translating languages
  • Making classifications and explaining what something does (such as defining the functionality of a code block). 

In other words, ChatGBT has the potential to simplify all kinds of everyday tasks for a lot of different people.

How does ChatGPT work?

Trained by AI and machine learning, the ChatGPT system is designed to provide information and answer questions through a conversational interface. ChatGPT’s AI is powered by a form of deep learning called neural networking. Neural networks are a series of algorithms that replicate the neuro functions of the human brain. Each of these neurons:

  • Receives data from the input layer
  • Processes it by performing calculations 
  • Transmits the processed data to another neuron

How data moves between neurons within a network and the calculations performed will depend on what data findings are uncovered along the way. Though a neural network makes decisions about what to do with data all by itself, it first needs to be trained with data inputs. ChatGPT’s AI has been trained with an enormous sample of written text taken from the internet. 

Who invented ChatGPT?

The research company who developed ChatGPT, OpenAI, said the new AI was created with a focus on ease-of-use. “The dialogue format makes it possible for ChatGPT to answer follow-up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests,” the company said in a recent statement. While chatbots are nothing new in the tech industry, the sophistication of ChatGPT makes previous iterations seem like child’s play by comparison. 

OpenAI is San Francisco-based, led by Sam Altman and receives financial backing from Microsoft, LinkedIn co-founder Reid Hoffman and Khosla Ventures. In what’s been a grim year for the tech sector, with mass layoffs, wrecked stock prices, high-profile cyber breaches and crypto catastrophes, ChatGPT has served as a timely reminder that the industry is still defined by jaw-dropping innovations.

A new era of natural language processing

Tech experts and venture capitalists have gushed about ChatGPT on Twitter, some even comparing it to Apple’s release of the first iPhone in 2007. Five days after ChatGPT was launched, Altman tweeted that the research tool had “crossed 1 million users!”. 

Back in 2016, tech bluechips like Facebook, Google and Microsoft were talking up their digital assistants as the future of human and AI interaction. They boasted of the potential for chatbots to book Uber rides, purchase plane tickets and answer customer service queries with a human touch.

Six years later, chatbot progress has been slower than expected. The majority of chatbots we interact with on a daily basis are still relatively primitive, often installed on customer help pages and only capable of answering rudimentary questions.

With early ChatGPT adopters demonstrating its ability to carry a conversation through multiple queries, deftly navigating a range of intricacies, the world of so-called natural language processing appears to be entering a new era. 

What does ChatGPT mean for employment? 

A person wrote this blog. Honestly. But how long before AI is able to write it instead?

In the days since ChatGPT was released, there’s been speculation that professions dependent on content production might be rendered obsolete, including everything from playwrights and copywriters to programmers and journalists.

Academics have generated responses to exam questions they admit would result in full marks if submitted by an undergraduate, and programmers have used ChatGPT to solve coding challenges in obscure programming languages in a matter of seconds.

However, in its current stage ChatGPT is not without its flaws. Its current knowledge base ends in 2021, rendering some queries and searches outside of its expertise. 

I asked it to write a blog article about “the future of employment factoring in the impact of ChatGPT” and was served a reply of “ChatGPT does not have the ability to provide information or opinions on current events or trends, or to speculate on the potential implications of new technologies”.

It’s also important to keep in mind that ChatGPT can occasionally give factually incorrect answers and authoritatively present the misinformation as truth, with OpenAI conceding that the AI can sometimes produce “plausible-sounding but incorrect or nonsensical answers”.

While ChatGPT might be able to generate a string of related facts, even presenting them in polished written language, it can’t be counted on to place those facts into dialogue and generate complex arguments. In short, critical-thinking and formulating opinions are not its biggest strengths. Without a doubt, it does have many others.  

OpenAI said the platform has “limitations and cannot replace humans”. If you’re in a profession that seems to be threatened by this emerging tech, wipe the sweat from your brow – AI isn’t taking over just yet.

The question remains though, how will ChatGPT be used by companies and people? The tech is versatile enough to be deployed in a wide range of settings to perform all kinds of tasks, so watch this space. One thing’s for sure – whatever ChatGBT is used for is bound to be groundbreaking.


advantages of service design

Academy Xi Blog

Advantages and benefits of using Service Design 2023

By Academy Xi

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advantages of service design

Service Design is now a major determinant of a brand’s survival and ability to stand out from the competition. Find out how designing services the right way can set a business up for success.

As users increasingly expect more personalised experiences, brands are now relying on Service Design to create innovative and relevant experiences for its people, partners, products, and processes.

According to Matt Kurowski, Service Designer and Co-Founder of Think5678, Service Design is the “intentional creation of valuable and impactful human experiences that create some kind of business or social value.”

Take advantage of the benefits of Service Design to stand out from the crowd. Here’s how Service Design can help your business or brand:

1. Design ideal human interactions

Utilising tools such as empathy maps and service blueprints, Service Designers are able to capture the entire end-to-end customer journey. By examining both an end user’s current experience and expectations, Service Designers are able to determine various pain points and moments of delight within a service.

service design advantages

There are five layers to designing for human interactions within Service Design:

  • A shift from product to service: Service Design requires a strategic shift of thinking from discrete, tangible products to a holistic and connected experience that caters to the customer.
  • Examining a product from back-end to front-end: This layer focuses on moving away from simply the end user or customer towards considering all stakeholders interested in, invested in, or influenced by a service.
  • Transitioning from consumption of a product to relationships: As the saying goes, people don’t buy a product but buy a better version of themselves. This mindset within Service Design focuses on building and nurturing sustainable and mutually beneficial relationships with customers.
  • Evolving from service to business design: From the holistic lens of a business, Service Design plays an important role in encouraging different levels of innovation within a company — whether it be incremental, adjacent, or disruptive.
  • Moving from relationships to ecologies: The Service Design ecosystem focuses on every individual or aspect involved and just as ecology is the link between an environment and its organisms, the value exchange in a service benefits everyone.

2. Consider everyone involved

Service Designers understand that delivering a great service is not only dependent on the service itself, but on the experience of people delivering that service. In this way, Service Designers aim to improve and innovate services that affect both customers and organisations.

Service Design enables companies to deliver experiences that create value for customers and allow for meaningful connections between the customer and the company. By reviewing all touchpoints and interactions that lie beneath a customer’s line of visibility, Service Design becomes the catalyst for innovation and future growth opportunities. By exploring the parts that make up an experience, businesses are able to identify opportunities for innovation from the inside, out.

Tools for understanding the different parties involved in a service include:

  • Research interviews: Talking to stakeholders to clarify the problem and define successful outcomes.
  • Stakeholder maps: A record of events’ that capture the interactions a customer has at different touchpoints of a service and helps break down the complexity of everyday interactions. Read more about Stakeholder Maps
  • User personas: An archetype or visual representation of a user trend that depicts customer behaviour and patterns. Download your free user persona template.

3. Create consistency with Service Design

The benefit of Service Design lies in its holistic process that aims to design a seamless and effortless solution for customers. Service Design ensures that the overall experience is consistent and easily understandable, with little to no friction for the customer between touchpoints.

service design benefits autralia

As a core pillar of design, creating consistency in a service is about making it intuitive. By examining all the areas of a service, Service Designers aim to increase the usability and learnability of the different aspects of that service.

The main benefits of improving the consistency of a service include:

  • Eliminating confusion: The more intuitive something is, the more user-friendly it is – effectively reducing error and eliminating user frustrations and pain points.
  • Improving wastage: A consistent service is built on predefined components which facilitates efficient decision making, reduces costs and time; rather than attempting to address changes for many variations, inconsistencies, and processes.
  • Encouraging continuous learning: By means of comparison, improved consistency forges a benchmark for businesses to learn and iterate. It is much easier to compare “apples to apples” within a service than making improvements across many moving parts.

4. Service Design embraces change

One of the major reasons that 90% of startups fail is creating a product that no one wants, also known as the inability to find product-market fit. Service Design improves companies’ chances of success by keeping them agile towards the constantly evolving needs of customers and changes in technology.

A Service Design led approach can help yield higher adoption and retention rates, as well as increase customer satisfaction. This drives increased revenue and market share in a highly competitive global market.

Through activities such as research, affinity mapping, empathy mapping and constructing a service blueprint, Service Designers are able to build and ideate a solution that is not only fit-for-purpose but also addresses the end user’s core job to be done.

5. Foster creativity and collaboration

By “stepping outside of the building” and going directly to end users, Service Design brings together all players in a service, thus drastically improving the collaboration and creativity of an end solution.

By removing stakeholders’ blinkers, Service Design injects a fresh perspective, incorporating various angles into a solution that include the client, customer, stakeholders and even external factors such as the environment.

Service Design considers how technology and products intersect and consider their relationship on a larger scale, providing an overarching view that would not be possible by simply looking at the immediate problem ahead.

6. Match organisational goals with customer needs

Service Design offers businesses a chance to align their organisational goals with customer needs. Following the logic of service design, what the customer wants should directly inform the goals that a business sets for itself. 

Companies often treat the customer’s needs as an opportunity to resolve or give additional value back to an original motive for purchasing a product or service. However, customer needs can also shape a business on a much broader scale. 

The ultimate objective of Service Design is to ensure that all of a business’s people, processes, resources and values are directed toward pleasing the customer. Any business that aligns its organisational goals with customer satisfaction is ultimately setting itself up for success.   

Want to learn how to deliver unforgettable services by focusing on the customer’s needs at every touchpoint? 

You can reap the benefits of using Service Design in your business or brand with our range of Service Design courses, which come in two flexible formats (part-time and self-paced) and offer you the chance to:

  • Access a comprehensive toolkit containing all the templates and tools a Service Designer needs
  • Demonstrate your strategic skills to employers by researching and creating an actionable current and future-state Service Blueprint 
  • Put the theory of Service Design into practice by working on weekly practical activities and hands-on projects                                                                                                                                      
  • Choose from a range of real-world scenarios or bring your own service design problem to solve.                                 
  • Add value in any business by Identifying customer needs, creating user stories and designing company-wide approaches that create exceptional service experiences 

Want to discuss your course options? Speak to a course advisor and take your first steps into the exciting world of design.

what is quantitative and qualitative data

Academy Xi Blog

Quantitative vs qualitative data: methods, differences and examples

By Academy Xi

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what is quantitative and qualitative data

In a nutshell, quantitative data is all about numbers and statistics, whereas with qualitative data we’re talking words and meanings. Read on to discover when to use which data research approach and what kind of methods you might consider.

What is quantitative data?

What is quantitative data

Data that is expressed as a defined amount, quantity or within a specific range is referred to as quantitative data. Quantitative data can be counted or measured, so it is common for the data to be stated with a unit of measurement. 

Some examples of quantitative data: kilograms when referring to the weight of something, or metres, kilometres or centimetres in reference to distance. Methods of quantitative research might include experiments or closed-ended question focused surveys.

What is qualitative data?

What is qualitative data

Qualities or characteristics of findings are described with qualitative data. This variety of information can be gathered using observation techniques, interviews, focus groups or questionnaires, and is often presented in a narrative format. Some examples of qualitative data: video recordings, case studies or interview transcriptions.

When to use qualitative vs. quantitative research

Ultimately, you will be best placed using a quantitative approach if you are needing to test to confirm something, such as a theory. 

Qualitative research is the way to go if you want to understand characteristics or traits of trends, or to determine the boundaries for larger data sets.

Both data research options enable you to answer different kinds of questions, so the choice you make will largely be driven by what you’re trying to answer or respond to.

There’s also the possibility of taking a mixed approach, again depending on what you’re trying to answer.

How are quantitative and qualitative data collected?

quantitative and qualitative data collection

Quantitative data collection

Qualitative data collection

Observation: watching within natural setting with no variable control

Publication reviews:Analysis of texts by various authors on the relevant topic areas

Experiments: variables controlled and manipulated to create cause and effect relationships

Ethnography: close observation of behaviours within a predetermined group for an ongoing period of time

Focus groups and surveys: interviewing with a closed question or multiple-choice approach

Focus groups and interviews: discussions within one-to-one and group settings to compile opinions, using open-ended questioning

How to analyse qualitative and quantitative data

When it comes to the analysis of data, the methods unsurprisingly alter for each data approach.

Quantitative data analysis

As we’re dealing with numbers, statistical analysis is often applied to establish data patterns, with outcomes plotted in graphs or tables.

Generally speaking, you could be looking to discover things such as average scores, reliability of results and how many times a certain answer was provided.

Preparation of the data before it is analysed is incredibly important. The data gathered needs to be validated, any known errors removed, and remaining data coded. This process ensures the best quality data is going to be analysed and provides a more accurate and helpful outcome.

The two most used quantitative data methods for analysis are inferential statistics and descriptive statistics.

  • Inferential statistics: show relationships between multiple variables, which means predictions can be made. Correlation explains the relationship between two variables, whereas regression shows or predicts the relationship between two. Analysis of variance tests how much the two variables differ from each other.
  • Descriptive statistics: provide absolute numbers, but don’t explain the reasoning or context behind them. Useful to apply when there is a limited amount of research available and mostly used for analysing single variables.

Qualitative data analysis

As we’re dealing with words, images or video content, qualitative data can be more challenging to analyse.

Examination of any recurring themes within the data is a helpful approach to take, as is exploring the frequency of use of phrases or words. The idea, like quantitative data analysis, is to discover patterns.

Methodologies which could be used include:

  • Grounded theory: establishing new theories from the data
  • Thematic analysis: identifying patterns in meaning to determine themes
  • Content analysis: interpretation of meaning from body content
  • Narrative analysis: discover how research participants construct story from their own personal experience

Best data collection tools & techniques

Now that we’ve looked at various approaches to gathering data, let’s look at some specific tools.

  • Qualitative data tools & techniques

While we might find ourselves using focus groups or interviews as a technique to collect data, tools such as ‘sentence completion’ or ‘word association’ can provide a wealth of further data to explore. With sentence completion, an individual is given a part-sentence to complete, and the answers provided give us an insight into the views and ideas of that person. Word association performs a similar function, where the individual is asked to share what comes to mind when they read or hear particular words.

  • Quantitative data tools

When it comes to drilling down into the digits, you might embrace statistical software options such as SPSS, JMP, Stata, SAS, R or MATLAB.

How to get into Data Analytics

Arm yourself with quality industry-aligned training that teaches you the process of collecting, organising, cleaning, and analysing raw data to identify patterns and draw conclusions.

With study options to suit all levels of ability, Academy Xi has you covered:

Do you have any questions? Our experienced team is here to discuss your training options. Speak to a course advisor today and take the first steps in your Data Analytics journey.

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