Industry-aligned content
This course has been built in consultation with experts from VisualNoise Data, so what you’ll learn is always current and industry recognised.
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AI Engineering- Advanced: Professional Certificate
Pay-in-full online from $13,050*(RRP $14,500)
From $0 per week
Gain the confidence to work with AI more comfortably in your role, with a real-world context and hands-on experience.
- Self-paced
- No prerequisites
- 12 months access, 480 hours
- Personal project
- Up to twelve 1:1 mentor sessions
- Payment plans available
- Digital Skills Masterclass Program
- Academic Support:18 hrs
*Save on our Professional Certificate courses when you pay in full!
We have a subscription model for all Professional Certificate courses.
Academy Xi students now have the option to subscribe to our entire range of Professional Certificate courses across all our portfolios for a monthly fee. Use this as a way to gain a wider digital skillset and give yourself an advantage as you compete for roles in the ever-changing employment landscape.
Our graduates are now the driving force behind some of Australia’s most innovative brands
Why choose this course?
No prerequisites or previous experience required
Launch your AI journey today, no matter what level of experience you have! Our beginner-friendly approach will help get you up to speed in no time.
Flexible and self-paced
With 6 months access, the speed at which you tackle online course content is up to you. Study at your own pace and fit learning into your busy lifestyle.
Created for Upskillers
Our Professional Certificate courses help you boost your career with sought-after AI Accelerator skills. Unlock higher salaries and job growth potential.
What your curriculum looks like
Upskill in AI Engineering – Advanced within 6 months. You’ll work through interactive online course content at your own pace, and have the support of an industry mentor when you need it.
- Module 1
- Module 2
- Module 3
- Module 4
- Module 5
- Module 6
- Module 7
- Module 8
Module 1
Recommended: 40 hours per module
Introduction to Python for AI
- Apply core programming methodologies to solve real-world problems using Python.
- Demonstrate scripting skills and structured logic using an industry relevant language.
Module 2
Recommended: 40 hours per module
Cloud Computing, Generative AI & Dashboards
- Build interactive dashboards using intermediate data science methodologies and industry-standard tools.
- Conduct exploratory data analysis across multiple datasets using SQL and table relations.
- Process large datasets using scalable tools such as PySpark and big data frameworks.
Module 3
Recommended: 40 hours per module
Introduction to Machine Learning
- Utilise intermediate machine learning modeling like decision trees and supervised learning.
- Prepare data for machine learning modeling with preprocessing (feature extraction) and normalisation.
- Utilise mathematics, statistics, and probability for data science methodologies to derive insights.
- Extract data from real databases
- Combine Python and SQL
Module 4
Recommended: 40 hours per module
Machine Learning with Scikit-Learn
- Utilise intermediate machine learning modeling like decision trees and supervised learning.
- Prepare data for machine learning modeling with preprocessing (feature extraction) and normalisation.
- Integrate mathematics, statistics, and probability for data science methodologies to derive insights.
Module 5
Recommended: 40 hours per module
Natural Language Processing, Time Series & Neural Networks
- Develop insights from language, time, and image data using neural networks and Natural Language Processing (NLP).
- Integrate mathematics, statistics, and probability for data science methodologies to derive insights.
Module 6
Recommended: 40 hours per module
Neural Networks & Similar Models
- Create an advanced neural network application.
- Integrate mathematics, statistics, & probability for data science methodologies to derive insights.
Module 7
Recommended: 40 hours per module
Large Language Models
- ML Models and the open-source MLOps Stack.
- Data-Centric Approaches for LLMs.
- Leveraging model fine-tuning and
prompt engineering to optimise output.
Module 8
Recommended: 200 hours
Artificial Intelligence Capstone
- In this intensive capstone, you will be tasked with developing 3 different portfolio projects and you will be expected to frame your projects around solving a business problem. You will bring together all of your skills from Core modules together to build 3 different methods: a regression model, a classification supervised model, and a classified unsupervised model.
Outcomes
- Apply Python programming and data science techniques to solve real-world problems.
- Design dashboards, analyse datasets, and work with large-scale data using SQL and PySpark.
- Build, evaluate, and optimise machine learning models using Scikit Learn and advanced methods.
- Apply Natural Language Processing, time series analysis, and neural networks to diverse data types.
- Leverage large language models with fine-tuning, prompt engineering, and MLOps practices.
- Deliver three portfolio-ready capstone projects that demonstrate AI solutions to business challenges.
What your curriculum looks like
Upskill in Data Analytics within 6 months. You’ll work through interactive online course content at your own pace, and have the support of an industry mentor when you need it.
- Module 1
- Module 2
- Module 3
- Module 4
- Module 5
- Module 6
- Module 7
- Module 8
- Module 9
- Module 10
Module 1
Recommended: 6-8 hours per module
Introduction to Data Analytics
Explore the value of data analytics, recognise types of problems answerable with data and cover some useful mindsets for approaching data. You’ll get familiar with the data analytics pipeline and use cases for key data tools.
- Recognise the value of data analytics
- Key terminology and tools relevant to the data space
- Awareness of data communication
- Apply introductory Excel skills
- Understand how Python is used in data analytics
- Apply the full data analytics pipeline to a data challenge
Module 2
Recommended: 6-8 hours per module
Define the problem
Understand the importance of connecting the high-level business objective (the ‘why’) with the objective for your data analysis. You’ll learn how to research the ‘problem domain’, write a problem statement and set success metrics.
- Define the problem, the problem domain and context
- Establish which insights are obtainable via data
- Translate business goals into data analysis goals
- Create a data analysis SMART goal
- Set expectations with stakeholders regarding data projects
- Apply basic Excel skills to a data problem Introduction to Python libraries
- Create a data analysis project statement of work
Module 3
Recommended: 6-8 hours per module
Get the data
Learn how to identify data for your analysis goals and the best data sources. You’ll uncover potential issues related to data collection, including data quality and ownership. You’ll also learn how to make queries to retrieve data from databases.
- Data licensing, ethics and privacy
- Obtain data from internal and external sources
- Relational databases
- Apply database skills by using Google BigQuery
- Write SQL queries
- Extract data from real databases
- Combine Python and SQL
Module 4
Recommended: 6-8 hours per module
Manipulate the data
Explore common data manipulation techniques, such as converting data types, sorting, filtering and managing duplicates. You’ll also learn how to work with various file formats, such as CSV and JSON.
- Understand statistical and computer science data types
- Identify different data file types such as CSV and JSON
- Apply common data manipulation techniques, such as converting data types, sorting, filtering and managing duplicates in Excel
- Apply these same data manipulation techniques in Python
Module 5
Recommended: 6-8 hours per module
Intro to charts
Learn how to use charts to explore data, discover new insights or form your own hypotheses. You’ll learn about different types of charts, how to build them, and how to use them to discover patterns and insights.
- Introduction to charts and data visualisations
- Identify charts for exploration and charts for communication
- Analyse types of charts and when each type is appropriate to use
- Understand the anatomy of a chart and chart elements
- Create charts using Excel and Python
- Use chart-creating tools such as Datawrapper and Tableau
Module 6
Recommended: 6-8 hours per module
Clean the data
Learn how to ensure your data is the best version of itself it can be. ‘Dirty’ data can lead to poor or misleading analysis results. By the end of the module, you’ll know how to identify dirty data and the techniques needed to clean it.
- Understand what ‘dirty’ data is Identify dirty data using Excel, with techniques such as filtering and summary statistics
- Clean dirty data using Excel and Python
Module 7
Recommended: 6-8 hours per module
Analyse the data 1
This module emphasises exploratory data analysis (EDA), which is a great approach for identifying patterns in data. You’ll learn how to combine data from multiple tables, use pivot tables to aggregate data, and answer specific questions using a combination of Excel and SQL.
- Understand the concept of EDA and the EDA mindset
- Visualise distributions, relationships and categorical variables
- Group and aggregate data using pivot tables and binning data
- Combine multiple data tables in Excel and SQL
- Apply EDA knowledge to the Python environment (optional)
Module 8
Recommended: 6-8 hours per module
Analyse the data 2
Get introduced to the practice of data modelling. You’ll learn why models exist, how they can add value to data analysis tasks, and how to identify different types of models. You’ll even take your first steps into modelling by building a few models of your own.
- Data modelling and regression basics
- Analyse trendlines and R-squared values
- Create a simple linear regression model in
- Excel Create a simple multiple regression and non-linear model in Excel (optional) Analyse regression fit and errors
- Managing the performance/complexity tradeoff
- Introduction to machine learning
Module 9
Recommended: 6-8 hours per module
Communicate the data (data visualisation)
Learn how to effectively communicate your findings. This brings the data analysis process full circle, as the outputs are tied back to the problem definition and used to effect change.
- Introduction to data storytelling and data dashboards
- Analyse data storytelling techniques
- Create data stories using Tableau and/or Datawrapper
- Apply techniques to communicate geographical data
Module 10
Recommended: 6-8 hours per module
Communicate the data (effecting change)
Focus on dashboard design and construction, covering use cases and the guiding principles for different dashboard builds. You’ll also review a number of sample dashboards and understand the suitability of various dashboarding tools.
- Analyse what makes an effective dashboard
- Explore different dashboard tools
- Create a simple dashboard in Excel or Tableau (optional)
- Examine best practice presentation skills, including understanding the audience and storytelling
- Create a presentation
Outcomes
- Unique project on a real-world dataset
- Experience using Excel, SQL, and Google BigQuery
- Visualisation and storytelling using Tableau & Datawrapper
- Exposure to Python, Google Colab & Plotly.py
- Industry recognised digital credential
Need more details about our AI courses?
Our course guides contain everything you need to know about our AI Accelerator courses, including…
- Topics covered
- How you’ll learn
- Course outcomes, and more!
Work 1:1 with an industry expert
All Professional Certificate students have access to an industry mentor as they progress through their course. Your mentor is an expert in the field and can provide insider tips and guidance on-demand.
- Access up to twelve 1:1 mentor sessions
- Get ongoing personalised feedback about your work
- Consult about project decisions and ask questions
- Interact via a dedicated Slack channel
“What a great 15 weeks! I've fallen in love with Data Analytics because of this course. It was sometimes difficult as a student who was completely new to the language and industry, but the mentor support helped heaps with that aspect. I'm very proud of my achievements and the projects I was able to create, which I can now display in my portfolio!”
Jocelyn Fisher, Data Analytics Transform 
Why study Data Analytics at Academy Xi?
Exclusive Masterclass program
Access a monthly webinar program designed specifically for our self-paced learners. Learn critical digital skills from industry experts, grow your network, and get advice from graduates now working in the field.
Hands-on experience
Get experience retrieving raw datasets, running SQL queries, manipulating data in Excel or Python, and creating data visualisations in Tableau.
Flexible coding options
Choose a level of coding exposure suited to your ambitions, with either a ‘low code’ route using Excel and SQL, or a more advanced coding approach that includes Python and SQL.
Custom analytics project
Bring all of your learnings together at the end of your course, and walk away with a unique dataset project that showcases your new skills.
Learn from the experts
Book up to twelve 1:1 sessions with an industry expert in Data Analytics to discuss course material, get personalised feedback and ask questions.
Fees & payment options
We offer a range of flexible payment options so you can achieve your goals today, and pay at your own pace.
No deposit
Study Now, Pay Later
Choose weekly, fortnightly or monthly repayments over a repayment term of up to 6 months, with no deposit and 100% interest-free.
Weekly repayments from
$0/week
PAYMENTS
From $55 /week
DISCOUNTED
Pay upfront
Pay for your course upfront to receive a discount on the full amount, and be eligible for any additional special offers.
Total cost of course
$13,050
TOTAL COST OF COURSE
$TBC $TBC
Student success stories
Our students come from different walks of life and have supercharged their careers, landing coveted jobs in the Design, Tech, and Marketing fields.
From Accountant to Data Analyst
Kanako Chapman
Kanako is a recent graduate of our Data Analytics: Elevate course. After 14 years in accounting, Kanako upskilled and moved internally into a new data analysis role that she’s really passionate about. Read on to find out about Kanako’s Academy Xi experience and how she managed to land an exciting new role auditing and analysing data in her company’s cost control department.
Kanako Chapman, Data Analytics Elevate
From Admin to Data Analytics
Jocelyn Fisher
With a passion for problem solving and an eye for detail, Jocelyn is a perfect match for a career in Data Analytics. Find out how the Data Analytics: Transform has helped Jocelyn go from complete beginner to industry-ready in just 15 weeks.
Jocelyn Fisher, Data Analytics Transform
From Physiotherapist to Software Engineer
Barry Nguyen
Startup Founder, Entrepreneur, Advisor — and now Physiotherapist turned Software Engineer — Barry Nguyen proves that curiosity, passion and continuous learning can help you get ahead of the curve.
Barry Nguyen, Software Engineering Transform
Some frequently asked questions
AI Engineering is the technical field of designing, building, and deploying AI systems that work at scale in the real world. It brings together software engineering, data science, and systems engineering principles to turn experimental models into functional applications or reliable machine-learning systems.
Studying this field allows you to gain a versatile technical skill set across Python, cloud computing, machine learning and NLP while learning to apply data-driven models to solve real business problems. It will also help you to prepare for high-demand roles in AI engineering, data science, and applied analytics.
The stackable nature of the program means you can build a professional portfolio and earn recognised credentials at the end.
Academy Xi offers a progressive three-stage pathway where each stage builds upon the last.
The Introductory certificate focuses on 120 hours of foundational Python, cloud tools, and core machine learning concepts.- The Intermediate stage expands to 280 hours and covers complex topics like neural networks, NLP, and Large Language Models.
- The Advanced certificate is a 480-hour comprehensive program where you apply all prior learning to design and deploy a complete AI solution through a Capstone project.
Learn more about the AI Engineering: Introduction and Advanced Certificates.
The Introductory certificate focuses on 120 hours of foundational Python, cloud tools, and core machine learning concepts.An AI Engineer builds and maintains the infrastructure that runs AI models. Their day-to-day work involves writing clean code to process large datasets, developing and training models, building entire AI applications, and ensuring those models are integrated into software products efficiently.
In this course, you’ll experience our ‘flipped classroom’ style of learning, where students cover course content independently before coming together to discuss concepts, ask questions and collaborate with mentor support. You’ll learn through a combination of:
- Readings
- Pre-recorded videos
- Regular live sessions with your mentor and peers
- 1:1 sessions with your mentor
- Hands-on activities and practical project work
- Q&A via chat and discussion boards
We offer three online course formats across design, tech and business that deliver a range of practical outcomes:
- Advanced Certificate courses teach job-ready skills and help you launch a new career
- Professional Certificate courses expand your existing skill set and progress your career
- Foundational Certificate courses teach introductory skills and build a knowledge base
To ensure our students secure their dream roles, we are proud to offer the Academy Xi Career Growth Guarantee for all Advanced Certificate courses. We assure your success with our placement rate, which means it is highly unlikely that you won’t get a role within the 180 day Career Support Program offered after graduation.
If for any reason you don’t secure a role within 180 days of your program, we will provide additional courses of your choice and additional career support – free of charge.
To find out if you qualify for our Career Growth Guarantee, please read the requirements outlined in our Terms & Conditions.
Have questions? We’re here to listen.
- Get support finding the right course for you
- Talk through course financing options
- Preview our learning platform
…and any other concerns!
