About AI and Machine Learning Masters Program

Sprintzeal's AI and Machine Learning Masters Program training in Brisbane covers hands-on projects, practicals, and access to hackathons, learning accessible to Python, Keras, Django, Tensor Flow, Flask, Amazon Sage Maker, NLTK, Alexa, OpenAI Gym. AI and Machine Learning Masters Program Certification in Brisbane helps to master key methodologies and enables professionals to develop related tools and apply AI and ML applicable to practical domains.

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Artificial Intelligence and Machine Learning - Demand and Career Scope

With a projected growth of over 15% in AI and machine learning jobs by 2029 (source: U.S. Bureau of Labor Statistics), this certification positions you for lucrative roles such as data scientist, AI engineer, and machine learning specialist.
The global AI market is anticipated to reach $190.61 billion by 2025 (source: Statista), and this certification equips you with the skills and knowledge to stand out in this competitive landscape, meeting the increasing demand for AI expertise across industries. 
The average salary of an AI and Machine Learning Expert is $171,715. By 2025, the AI market is expected to grow to a $190 billion industry creating millions of job opportunities

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Live Online Training

A$ 7164 A$10746

  • Expert-Led Learning with Personalized Guidance.
  • Exclusive Access to Study Materials, Labs and Toolkit 
  • Master Python, Pandas, Keras, and 10 Other Tools
  • Acquire Industry Recognized AI and ML Certification
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Course Agenda

Course Agenda

Company Brochure

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AI and Machine Learning Masters Program

Internationally Recognized AI and Machine Learning Course by Sprintzeal


Our AI and Machine Learning Masters Program covers a comprehensive range of topics, from the fundamentals of AI to advanced machine learning techniques. Dive into supervised and unsupervised learning, neural networks, and explore the capabilities of large language models. Practical exercises and industry case studies ensure a well-rounded learning experience.


In this course, you will learn the latest AI technologies, Speech Recognition, Machine Learning, Deep Learning, Language Processing, and more. You can download our Course Syllabus to get full details of the topics covered and skills offered in this course. This course is aimed at equipping learners with the knowledge and skills necessary for building a successful career in the field of Artificial Intelligence and Machine Learning.


Upon completion of our AI and ML course, you will unlock a world of career opportunities as a data scientist, AI engineer, machine learning engineer, and more. Industries across sectors are actively seeking AI professionals to drive growth and innovation.


AI and ML Tools


What Technical Skills Will You Gain?

- Proficiency in Python programming for AI and ML applications.
- Data preprocessing techniques to clean and transform data effectively.
- Building and evaluating various machine learning models.
- Implementing neural networks and deep learning architectures.
- Image classification and recognition using Convolutional Neural Networks (CNNs).
- Natural Language Processing (NLP) skills for text analysis and sentiment analysis.
- Clustering and dimensionality reduction for unsupervised learning.
- Working with large language models and fine-tuning them for specific tasks.
- Ethical considerations in AI technology deployment.
- Hands-on experience with industry-standard AI and ML tools and libraries.


Day 1: Introduction to AI & ML

  • Hour 1-2: AI vs ML vs Deep Learning: Definitions and Differences
  • Hour 2-3: Importance and Applications of AI & ML
  • Hour 3-4: Setting up the Environment (Python, Jupyter Notebook, Libraries)
  • Hour 4-8: Python Refresher: Essential Libraries for ML (NumPy, pandas)

Day 2: Supervised Learning - Basics

  • Hour 1-2: Introduction to Supervised Learning
  • Hour 2-3: Linear Regression
  • Hour 3-6: Logistic Regression, Naive Bayes, KNN
  • Hour 6-8: Hands-on: Building & Evaluating Regression Models

Day 3: Supervised Learning - Advanced

  • Hour 1-2: Decision Trees and Random Forests
  • Hour 2-3: Support Vector Machines (SVM)
  • Hour 3-6: Ensemble Methods: Boosting, Bagging
  • Hour 6-8: Hands-on: Classification Problems & Model Evaluation

Day 4: Unsupervised Learning

  • Hour 1-2: Introduction to Unsupervised Learning
  • Hour 2-4: Clustering: K-means, Hierarchical
  • Hour 4-6: Dimensionality Reduction: PCA, t-SNE
  • Hour 6-8: Hands-on: Clustering and Visualization

Day 5: Neural Networks and Deep Learning - Basics

  • Hour 1-2: Introduction to Neural Networks
  • Hour 2-3: Forward and Backward Propagation
  • Hour 3-4: Activation Functions, Loss Functions
  • Hour 4-8: Hands-on: Building a Basic Neural Network with TensorFlow/Keras

Day 6: Convolutional Neural Networks (CNNs)

  • Hour 1-2: Introduction to CNNs
  • Hour 2-3: Image Classification and Feature Learning
  • Hour 3-4: Pooling, Flattening, and Full Connection
  • Hour 4-8: Hands-on: Image Recognition Tasks with CNNs

Day 7: Recurrent Neural Networks (RNNs) and Natural Language Processing

  • Hour 1-2: Introduction to RNNs and LSTM
  • Hour 2-5: Basics of Natural Language Processing (Tokenization, Embedding, TfIdf, Bag of Words)
  • Hour 5-6: Sequence Models and Attention Mechanism
  • Hour 6-8: Hands-on: Text Generation and Sentiment Analysis

Day 8: Dive into Large Language Models (LLMs)

  • Hour 1-2: Introduction to LLMs
  • Hour 2-3: Inner Workings of GPT-style Models
  • Hour 3-4: Training and Fine-tuning LLMs
  • Hour 4-5: Practical Applications of LLMs
  • Hour 5-6: Ethical Considerations and Limitations
  • Hour 6-7: Hands-on Session: Using Pre-trained LLMs
  • Hour 7-8: Advanced Topics & Wrap-up

Prerequisites for AI and Machine Learning Master’s Program

  • Candidates must have a bachelor’s degree with an average score of 50% or more
  • Understanding of basic concepts in programming, statistics and mathematics is required
  • Candidates with 2+ years of working experience in AI and Machine learning are advised to take up this course. Nevertheless, having work experience is not mandatory and candidates with no experience can also apply.


Note - Candidates are advised to have knowledge of Python before taking up this course. We offer a free pre-course session for candidates who do not have knowledge about python to help them understand the master program better.

Talk to our Master’s Program Counselor in AI and Machine Learning certification for a better understanding of the scope and application process of this AI and Machine Learning course. We have a team of dedicated experts at Sprintzeal who will guide you with the master program details, application process, and other essential queries.

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Course Completion Rate 70.1%

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AI and Machine Learning Masters Program

Artificial intelligence technologies and machine learning are being adopted by booming businesses and industries all over the world. With this sudden rise in the market, there is a shortage on AI and machine learning specialists in various parts of the world. Taking up AI and Machine Learning courses can help candidates benefit from this current market scenario, get high paying jobs and have a successful career.

Sprintzeal’s Master Degree program in AI and Machine Learning is one of the most trusted and best AI and Machine Learning certification in Australia . This AI and Machine Learning certification is designed by industry experts and comes with several benefits like best price guarantee, flexible schedules, interactive sessions, hands-on projects, access to hackathons and more.

Below are the Eligibility Criteria for AI and Machine Learning training program

  1. Bachelor’s degree holder with an average score of 50% or more
  2. A foundational understanding of concepts in programming, statistics, and mathematics.
  3. Two or more years of work experience in AI and Machine learning certification (preferred)

Sprintzeal’s AI and Machine Learning master’s program follows a simple four-step admission process.

  1. Fill out the application form and submit it for review
  2. After the application is reviewed by our counselors, confirmation is provided
  3. A candidate is requested to pay the course fee and enroll in the batch of their choice
  4. Get started with AI and Machine Learning Master Program

Sprintzeal’s AI and Machine Learning Master’s Program is designed by industry experts considering the latest AI and machine learning trends and technologies. It is a full fledge 12 month course with several benefits for candidates undergoing training. On completion of the course, a globally recognized Master’s Program AI and Machine Learning Certification are awarded to candidates.

Below is the list of technologies candidates are exposed to in order to improve their AI skills, Machine learning and deep learning techniques, Natural language processing, Computer vision, Neural networks, Generative adversarial networks and more. This AI and ML course is designed by industry experts. It is aimed at enhancing a professional’s knowledge and helping him/her become an AI and ML expert.

Most of the AI and Machine Learning training courses require candidates to have a bachelor’s degree with 50% or more score. Candidates with work experience in Artificial intelligence field or machine learning are preferred. However, it is not compulsory to have work experience in this field. Graduates interested in making a career in AI and machine learning can also take up this course.

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Where our Alumni Work

Sprintzeal AI and Machine Learning Masters Program in Brisbane, Australia Certificate Holders work at 1000s of companies like

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Frequently Asked Questions

After finishing the course, the candidate is awarded a Masters Program in AI and Machine Learning certification.

Sprintzeal’s master program is considered one of the best AI and ML courses for its high quality training and support. It comes with study materials, audio-video lectures from expert trainers, practice tests, and 24x7 support via chat and email throughout the course.

AI and Machine Learning Master’s Program is equipped with Global teaching assistance for candidates enrolling for the course. We offer 24/7 support to customers and participants willing to or already undergoing AI and Machine Learning training program with Sprintzeal. Participants can reach out to us for support via email, chat, and phone. Our dedicated team will help you with queries, and resolve issues to help you get the most out of your training. 

Candidates must enroll for the course, finish all sessions and clear the exam to earn the Master’s Program AI and Machine Learning Certification.


Our course advisors and support team are available 24x7 to help candidates undergoing training for Masters Program in AI and Machine Learning. Candidates can reach us with their issues and queries via chat, email or call option.

Yes, candidates can cancel their training if required. We also offer rescheduling option. Plus, for candidates who wish to cancel their AI and Machine Learning training, the refund amount after deducting administration fee is also provided.

Yes, certifications provided by Sprintzeal are internationally recognized. All the courses are accredited by internationally recognized governing bodies and are registered trademarks of the institute.

On completion of the AI and Machine Learning course, candidates will be considered a part of Sprintzeal’s alumni. This makes them eligible for extra benefits and exclusive offers.

Yes, candidates can access AI and ML courses content at any time. They can access AI and Machine Learning training content even after completion of the course.

Although a basic understanding of AI, statistics, and programming is advised, it isn’t mandatory. Candidates with no work experience or technical knowledge in AI can also apply for AI and Machine Learning courses.

Candidates with bachelor’s degree and those willing to make a career in this field can enrol in Sprintzeal’s AI and Machine Learning course. This Masters program offers both foundational and advanced AI and Machine Learning skills.

AI and Machine Learning Certification course offers in-depth knowledge about both basics and latest advancements in Artificial Intelligence and Machine Learning. Some of the important concepts learned in this course are NLP, Speech recognition, GANs, Tensor flow, NumPy, and more

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