Master of Artificial Intelligence and Machine Learning

Transform your career with our comprehensive 12-month Master’s program in Artificial Intelligence and Machine Learning, certified by UCAM University, Spain. This professional development program equips you with in-demand skills in Python programming, data analytics, machine learning, and AI implementation through 200 hours of live instructor-led training.

12 Months

6 Modules

6 Assignments

Blended Learning

3 Projects

Advanced

Globally Recognized & Accredited:

15000

Students Trained Globally

Industry-Aligned Programs

Countries with Active Alumni

Career Transition Success

Tools & Technologies That Power Success

Master the complete data science ecosystem with hands-on experience using industry-leading tools and frameworks. Our Advanced Program in Data Science equips you with practical skills in Python programming, data manipulation, visualization, and machine learning – preparing you for real-world data challenges.

Python

MySQL

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Tools & Technologies That Power Success

Master the complete AI and machine learning ecosystem with hands-on experience using industry-leading tools and frameworks. Our Master’s Program in AI & ML equips you with practical skills in Python programming, data manipulation, visualization, and machine learning algorithms – preparing you for real-world AI challenges.

Python

MySQL

Anaconda

Jupyter Hub

TensorFlow

NumPy

Seaborn

Matplotlib

Excel

GIT

Tableau

Google Colab

Universidad Católica de Murcia, Masters Degree

Universidad Católica de Murcia (UCAM), founded in 1996, is a fully-accredited European University based out of Murcia, Spain. With learning centres in the Middle East and Southeast Asia, UCAM aims to provide students with the knowledge and skills to serve society and contribute to the further expansion of human knowledge through research and development. The university offers various courses, including 30 official bachelor’s degrees, 30 master’s degrees and ten technical higher education qualifications through its Higher Vocational Training Institute, in addition to its in-house qualifications and language courses. The programmes offered are distinguished in Europe and worldwide, with good graduate employability prospects as well. UCAM is accredited by ANECA (National Agency for Quality Assessment and Accreditation of Spain) and the Ministry of Education regarding 17 of its undergraduate degrees.

Eligibility

Students seeking admission to this Master’s program must fulfill the following criteria: A Bachelor’s degree from a recognized institution, proficiency in the English language, and fundamental computer literacy to navigate the digital learning environment. The course is designed to accommodate beginners, providing foundational AI and Business concepts before advancing to complex topics.

Prerequisites

Good to have familiarity with basic concepts of mathematics and programming knowledge. Basic knowledge of statistics and analytical thinking will be a plus. However, no prior AI or machine learning experience is required as our comprehensive curriculum starts from fundamentals.

Course Modules

Introduction to Ai and ML

Specialization Module 1

Advanced Python and ML for NLP

Specialization Module 2

Advanced Python and ML for CV

Capstone Projects

Industry based projects

Foundations of Python Programming

Begin your data science journey with a solid grounding in Python. Learn how to install and configure the Python environment, understand its simple syntax, and explore the essentials—variables, data types, and operators that form the building blocks of programming.

Control Flow and Core Data Structures

Gain hands-on experience with Python’s core control tools such as conditionals, loops, and functions. Understand and implement key data structures like lists, tuples, and dictionaries, essential for efficient data handling and logic building.

Applied Python for Data Science

Delve into Python’s powerful libraries—NumPy, Pandas, and Matplotlib—to treat, manipulate, and visualize data. Build confidence in writing clean, functional scripts that serve as the foundation for advanced analytics and machine learning.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this module, you will:

Understand and apply Python syntax, variables, data types, and operators
Use lists, tuples, dictionaries, and control flow statements to build logic
Write reusable Python functions to solve data-driven problems
Work with libraries like NumPy, Pandas, and Matplotlib for data analysis
Develop confidence to use Python in machine learning and data science contexts

Core Math Foundations for AI

Build a strong mathematical base essential for understanding how AI systems work. Explore key topics such as linear algebra, calculus, and probability theory—each critical for grasping the inner workings of machine learning algorithms and intelligent systems.

Statistical Thinking and Data Interpretation

Master descriptive and inferential statistics to analyze real-world data. Learn how to formulate and test hypotheses, draw insights, and make evidence-based decisions. Develop the ability to interpret patterns and variability in complex datasets.

Mathematics in Action with Python

Translate theory into practice using Python libraries such as NumPy, Pandas, and Matplotlib. Visualize trends, analyze correlations, and apply statistical tools to build the foundation for evaluating and optimizing AI models.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this module, you will:

Use NumPy, Pandas, and Matplotlib to manage and visualize data
Apply descriptive and inferential statistics to draw meaningful insights
Formulate hypotheses and validate them with real-world datasets
Understand and apply probability theory and Bayes’ theorem
Perform correlation and regression analysis to support AI modeling decisions

Python as the Backbone of AI Development

Explore Python’s power and flexibility in AI applications. Work with essential libraries like NumPy, Pandas, and Scikit-Learn to manipulate data, implement machine learning models, and streamline your AI development pipeline through hands-on coding exercises.

Data Collection, Cleaning, and Preprocessing

Master critical steps in preparing data for analysis. Learn to handle inconsistencies, missing values, and formatting errors in both numerical and text data. Understand the preprocessing techniques that ensure data quality and reliability in machine learning workflows.

Exploration, Modelling & Pattern Recognition

Dive into Exploratory Data Analysis (EDA), clustering, classification, and pattern discovery. Learn how to transform raw data into structured datasets ready for training algorithms and build predictive models with confidence using Python’s ML stack.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this module, you will:

Understand the role of EDA, data cleaning, and preprocessing in ML workflows
Apply Python libraries (NumPy, Pandas, Matplotlib, Scikit-learn) to real-world data
Perform effective preprocessing on both numerical and text datasets
Gain hands-on experience with clustering and classification techniques
Identify patterns and transform raw data into actionable insights for model building

Foundations of Artificial Intelligence

Explore the core concepts of Artificial Intelligence and Machine Learning. Understand how machines learn from data without explicit programming, and gain insights into the real-world applications, challenges, and ethical considerations of AI across industries.

Supervised and Unsupervised Learning Techniques

Learn how to select and apply machine learning algorithms including linear regression, k-NN, decision trees, logistic regression, and random forest. Understand the differences between supervised and unsupervised learning and when to apply each technique.

Model Development, Evaluation & Ethics

Discover the complete ML workflow—from data preprocessing to model training, testing, and evaluation. Learn how to measure model performance using precision, recall, accuracy, and F1-score. Explore the ethical and practical aspects of AI adoption.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this module, you will:

Understand the foundational principles of AI and machine learning
Recognize the ethical, social, and legal challenges associated with AI
Differentiate between supervised and unsupervised ML techniques
Select appropriate algorithms for various business and data types
Train and test ML models using practical datasets
Evaluate models using precision, recall, F1-score, and accuracy
Gain insight into the mathematical logic behind core ML algorithms

Mathematics & Machine Learning Foundations for NLP

Explore multivariate calculus and optimization techniques using Python to power resilient NLP systems. Understand how core mathematical intuitions—limits, series, and discrete optimization—shape intelligent language models and processes.

Hands-On NLP with Python & NLTK

Use Python’s Natural Language Toolkit (NLTK) for tokenization, parsing, entity recognition, and lemmatization. Extract key insights from text such as synonyms, antonyms, and patterns for building powerful ML-based NLP systems.

Neural Networks & Deep Learning Applications

Apply traditional and deep neural networks (FNNs, RNNs, CNNs) to NLP tasks like utterance classification and sequence tagging. Build advanced speech-based applications, from speech-to-text to automated speech recognition and deployment.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this specialization, you will:

Acquire advanced Python skills for NLP applications
Work with NLP packages to preprocess, vectorize, and analyze text
Develop machine learning models for speech recognition and conversion
Apply deep learning architectures like CNNs and RNNs to NLP use cases
Understand the application of mathematical modeling in language processing
Deploy automated NLP solutions for real-world language problems

Foundations of Image Processing & Deep Learning

Begin with image handling using the NumPy and OpenCV libraries to perform operations like color mapping, thresholding, gradients, and more. Learn the basics of video processing, webcam feeds, and the fundamentals of how machines “see” using Python.

Deep Learning & Computer Vision Models

Leverage neural networks—CNNs and RNNs—to build deep learning models for image and video recognition. Understand how to apply TensorFlow, Keras, and the Faster-RCNN-Inception-V2 model for identifying objects, people, and patterns within visuals.

YOLO, Clustering & Deployment in CV

Develop automated CV systems using real-time object detection techniques like YOLO. Explore both supervised and unsupervised ML algorithms such as K-Means and SVMs in CV applications. Work within the Anaconda environment to build, test, and deploy solutions.

Learning Outcomes

Module Duration: 4–6 weeks

By completing this specialization, you will:

Understand key concepts of computer vision and image processing in Python
Use OpenCV and Pillow for working with images and live video feeds
Develop deep learning models using CNN and RNN architectures
Create real-time CV applications using YOLO and TensorFlow
Understand the lifecycle of a deep learning model in CV projects
Apply SVMs, KNN, and K-means clustering for image-based ML tasks
Deploy object recognition systems using modern frameworks

Solving Real-World Problems with AI & ML

Work closely with industry mentors to design and implement AI/ML-driven solutions for real business challenges. Learn to identify critical problems, gather relevant data, and apply appropriate algorithms to solve high-impact use cases across industries like healthcare, finance, retail, and manufacturing.

Professional Collaboration and Project Execution

Gain exposure to industry-grade project management techniques. Develop, test, and evaluate AI solutions while effectively communicating with stakeholders. Build strong problem-solving and time management skills through structured methodologies and hands-on execution.

Career-Ready Application and Industry Impact

This capstone equips students with practical skills in end-to-end solution development, stakeholder engagement, and outcome measurement—offering unmatched real-world experience and exposure to potential employers across diverse sectors.

Learning Outcomes

Project Duration: 8–12 weeks

By completing this capstone, you will:

Apply AI & ML methodologies to solve complex, industry-specific problems
Design and deploy AI/ML solutions from concept to implementation
Collaborate with industry stakeholders in a professional setting
Evaluate the real-world impact and effectiveness of AI/ML systems
Develop project management, communication, and data-driven decision-making skills

Your Success Story Starts Here

Every image here tells a story of transformation, dedication, and success. Be the next to wear the cap and gown. Enroll today, and let your journey begin.

What Our Students Say

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

Pemsith Ravi

Thanks to the support of this prestigious institution – airtics. I was able to earn a master’s degree in data science. I had a fantastic educational experience there, and they possess a highly competent and knowledgeable lecturing panel. Anyone looking to make it major in the data science field should enrol in their course.

Zeeshan Ali

Airtics offers a truly transformative learning experience. The course content is up-to-date, the mentors are incredibly supportive, and the flexibility of the online platform made it easy to balance with my work. Highly recommended for anyone looking to upskill!

Aalaa Shbair

The experience at Airtics College has been tremendous for me. It has illuminated my path and opened the way for me to become a developer of solutions in my workplace. I cherish every moment of this online learning experience and the supportive community of instructors and peers.

Muhammad Fatouh

Airtics offered a great platform that allowed me to take a meaningful step forward in data science while balancing my demanding job as a telecom engineer. If you have a busy schedule and struggle with work-life balance, I encourage you to find a flexible platform like Airtics to pursue your goals.

Al Tayyab Bakhsh

Coming from a non-technical background in marketing, switching to data science was challenging. The faculty at Airtics was incredibly helpful, especially my mentor Miss Piyali, who guided me with patience every step of the way. Their mentorship gave me the confidence to succeed.

Dilnawaz Qureshi

Airtics provides an impressive curriculum for Python Full Stack development that is both well-structured and up-to-date. This comprehensive approach ensures we acquire a thorough understanding of the field and are well-prepared for real-world challenges.

Charuhaas Shenoy

Madonna Ghanem

The resources provided by Airtics for AI and ML students are top-notch. The institute has a well-equipped virtual lab with the latest software, allowing us to experiment with complex algorithms. The online library offers a wide range of reference materials and research papers.

Dhruv Narse

Airtics provides a conducive learning environment for data analytics students. They have experienced faculty, and provide access to the latest software and tools used in the industry. This ensures that we are well-prepared for our future careers in the field.

What Our Students Say

Pemsith Ravi

Zeeshan Ali

Aalaa Shbair

Muhammad Fatouh

Al Tayyab Bakhsh

Dilnawaz Qureshi

Charuhaas Shenoy

Madonna Ghanem

Dhruv Narse

Real-World Capstone Projects

Apply your AI and machine learning skills to solve real business challenges through hands-on industry-based projects. Choose from our curated capstone projects across healthcare, finance, retail, manufacturing, and technology sectors, or bring your own organizational problem to create a portfolio that showcases your expertise to future employers.

Predictive Healthcare Analytics

Build a machine learning model to predict disease risk and treatment outcomes using patient data, medical history, and diagnostic parameters for improved healthcare decision-making.

Computer Vision System

Develop an advanced computer vision solution using deep learning and CNN algorithms to automatically detect, classify, and analyze visual data for real-world applications.

Business Intelligence Dashboard

Create interactive business dashboards that transform raw organizational data into actionable insights, predictive analytics, and visual reports for strategic decision-making.

Learn from Industry Leaders & Experts

Learn from the best in the field. Our faculty combines academic brilliance with industry expertise, featuring PhD holders, senior data scientists, and AI researchers from top organizations.

Ms. Piyali Mondal Head of Department

Ms. Priti Mondal Associate Faculty

Dr. Abdullah El-Nokiti Professor

Dr. Mohd Merajuddin Inamdar Professor

Dr. Madhavi Vaidya Professor

Dr. Poonam Chaudhari Professor

Dr. Anup Kumar Maurya Professor

Dr. Milan Amrutkumar Joshi Industry Expert

Dr. Mohamed Elhaw Industry Expert

Dr. Pradeep Tiwari Industry Expert

Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our Advanced Program in Data Science. Learn about program details, requirements, and what to expect from this 6-month certification course.

Why should I join the Master of AI & ML program?

This comprehensive 12-month Master’s program combines theoretical foundations with practical applications of AI and machine learning. You’ll gain expertise in Python programming, data analytics, machine learning algorithms, and AI implementation through 200 hours of live instruction, industry-based projects, and hands-on experience with cutting-edge tools like TensorFlow, Scikit-Learn, and advanced neural networks.

What if I fail to attend the live classes?

All live sessions are recorded and available through our advanced Learning Management System (LMS). You can access recorded lectures, review materials, and catch up on missed content at your convenience. Our flexible learning format is designed to accommodate working professionals with busy schedules.

How does AI & ML differ from traditional Data Science programs?

While traditional data science focuses primarily on data analysis and statistics, our AI & ML program goes deeper into artificial intelligence algorithms, neural networks, computer vision, natural language processing, and advanced machine learning techniques. You’ll learn to build intelligent systems that can learn, adapt, and make autonomous decisions.

What can I expect from the Master of AI & ML program?

You’ll complete 6 comprehensive modules covering Python programming, mathematics for AI, machine learning algorithms, specialized tracks in NLP and Computer Vision, plus industry-based capstone projects. The program includes 3 real-world projects, 6 assignments, 6 case studies, and mentorship from experienced industry professionals and academics.

Who can join this program?

Anyone with a Bachelor’s degree, proficiency in English, and basic computer literacy can join. The program is designed for beginners and accommodates professionals from various backgrounds. No prior AI or machine learning experience is required as we start from foundational concepts.

Do I need prior coding experience to learn this program?

No prior coding experience is required. Our curriculum starts with “Basics of Python” in Module 1, covering programming fundamentals, data types, operators, and control structures. We build your programming skills progressively throughout the program.

What are the current capabilities of Artificial Intelligence?

Today’s AI systems excel in areas like computer vision, natural language processing, predictive analytics, automated decision-making, and pattern recognition. AI is transforming industries including healthcare (diagnostic imaging), finance (fraud detection), retail (recommendation systems), and manufacturing (predictive maintenance).

What is the future of Artificial Intelligence?

AI is evolving toward more sophisticated applications including autonomous vehicles, advanced robotics, personalized medicine, smart cities, and general artificial intelligence. The field offers tremendous career opportunities in AI research, machine learning engineering, data science, and AI product development across all industries.

What university certification will I receive?

You’ll receive a Master’s degree in Artificial Intelligence and Machine Learning from Universidad Católica de Murcia (UCAM), Spain – a fully accredited European university. This degree can be attested in most nations and accepted for academic validation globally.

What career opportunities are available after completion?

Graduates can pursue roles as AI/ML Engineers, Data Scientists, AI Research Scientists, Computer Vision Engineers, NLP Specialists, AI Product Managers, and AI Consultants. Our 94%+ placement record and strong industry partnerships help students transition into high-demand AI careers.

Still have questions?

If you have any other questions or need further information about our Master of Artificial Intelligence and Machine Learning program, don’t hesitate to contact us. Our admissions team is here to help you take the next step in your AI and machine learning career.

Why Read Our Blog?

Our blog offers a wealth of knowledge and practical advice to help you

Master of Artificial Intelligence and Machine Learning

Globally Recognized & Accredited:

Tools & Technologies That Power Success

Anaconda

Jupyter Hub

Pandas

NumPy

Tools & Technologies That Power Success

Anaconda

Jupyter Hub

TensorFlow

NumPy

Universidad Católica de Murcia, Masters Degree

Eligibility

Prerequisites

Course Modules

Foundations of Python Programming

Control Flow and Core Data Structures

Applied Python for Data Science

Learning Outcomes

Core Math Foundations for AI

Statistical Thinking and Data Interpretation

Mathematics in Action with Python

Learning Outcomes

Python as the Backbone of AI Development

Data Collection, Cleaning, and Preprocessing

Exploration, Modelling & Pattern Recognition

Learning Outcomes

Foundations of Artificial Intelligence

Supervised and Unsupervised Learning Techniques

Model Development, Evaluation & Ethics

Learning Outcomes

Mathematics & Machine Learning Foundations for NLP

Hands-On NLP with Python & NLTK

Neural Networks & Deep Learning Applications

Learning Outcomes

Foundations of Image Processing & Deep Learning

Deep Learning & Computer Vision Models

YOLO, Clustering & Deployment in CV

Learning Outcomes

Solving Real-World Problems with AI & ML

Professional Collaboration and Project Execution

Career-Ready Application and Industry Impact

Learning Outcomes

Your Success Story Starts Here

What Our Students Say

Pemsith Ravi

Zeeshan Ali

Aalaa Shbair

Muhammad Fatouh

Al Tayyab Bakhsh

Dilnawaz Qureshi

Charuhaas Shenoy

Madonna Ghanem

Dhruv Narse

What Our Students Say

Pemsith Ravi

Zeeshan Ali

Aalaa Shbair

Muhammad Fatouh

Al Tayyab Bakhsh

Dilnawaz Qureshi

Charuhaas Shenoy

Madonna Ghanem

Dhruv Narse

Real-World Capstone Projects

Predictive Healthcare Analytics

Computer Vision System

Business Intelligence Dashboard

Learn from Industry Leaders & Experts

Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Still have questions?

Why Read Our Blog?

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