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PG Diploma in Data Science and Artificial Intelligence

Master the fundamentals of data science and AI with our comprehensive 6-month PG Diploma program, certified by UCAM University, Spain. This industry-focused program combines Python programming, statistical analysis, machine learning, and business intelligence through 200 hours of live instructor-led training and hands-on projects.
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  • Duration

6 Months

  • Modules

5 Modules

  • Assignments

6 Assignments

  • Format

Online Learning

  • Projects

3 Projects

  • Level

Intermediate

Globally Recognized & Accredited:

15000

Students Trained Globally

25

Industry-Aligned Programs

70

Countries with Active Alumni

87

Career Transition Success

  • Industry-Standard Technology Stack

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.

  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

MySQL

learn anaconda

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Join Airtics Education
  • Industry-Standard Technology Stack

Tools & Technologies That Power Success

Master the complete data science ecosystem with hands-on experience using industry-leading tools and frameworks. Our PG Diploma in Data Science and Artificial Intelligence equips you with practical skills in Python programming, data manipulation, visualization, and machine learning – preparing you for real-world data challenges.
  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

MySQL

learn anaconda

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Join Airtics Education

Universidad Católica de Murcia,
PG Diploma

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

Eligibility

This course is well suited for participants of all levels of experience because of the high demand for Data Science with Python programmers. Data Science with Python is beneficial for analytics professionals interested in Python, software and IT professionals interested in Analytics, as well as anyone with a genuine interest in Data Science.

Prerequisites

Good to have familiarity with basic concepts of mathematics and programming knowledge. Basic knowledge of Database tools and workflow will be a plus.

Course Modules

Module 1
Python for Data Science
Module 2
Mathematics and Statistics for Data Treatment
Module 3
Data cleaning and pre-processing
Module 4
Introduction to Machine Learning
Specialization Module
ML Deployment ()
Python Basics and Core Concepts
Python Basics and Core Concepts

Learn fundamental Python programming including variables, data types, conditional statements, loops, and functions. Master the building blocks essential for data science applications.

Essential Python Libraries
Essential Python Libraries
Explore NumPy for numerical computing, Matplotlib for data visualization, and Pandas for data manipulation. Gain hands-on experience with the most important data science tools.
Practical Programming Skills
Practical Programming Skills
Develop the ability to write efficient Python scripts for data analysis. Practice with real-world examples and build confidence in problem-solving using code.
Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing this foundational module, you will:

  • Master Python programming structure and learn how to write efficient programs for data analysis
  • Understand core Python concepts including syntax, functions, and conditional statements for problem-solving
  • Acquire essential Python skills to transition into specialized branches like Machine Learning and Data Science
  • Gain proficiency with key libraries (NumPy, Pandas, Matplotlib) to write scripts for data manipulation and analysis
Mathematical Foundations
Mathematical Foundations

Master linear algebra, probability theory, statistics, and statistical tools. Build the mathematical foundation required for advanced data analysis and machine learning algorithms.

Data Formats & Tools
Data Formats & Tools
Learn to work with CSV files and Excel spreadsheets. Understand different data formats and how to efficiently import, export, and manage data across various platforms.
Data Cleaning & Preparation
Data Cleaning & Preparation
Develop skills to identify and fix data quality issues including incorrect, corrupted, duplicate, or incomplete data. Master data preprocessing for reliable analysis.
Learning Outcomes
Module Summary Duration: 3-4 weeks

By completing this module, you will:

  • Master statistical tools for working with datasets effectively
  • Learn the essentials of probability and statistics for data analysis & visualization
  • Know how to import and clean data using libraries like NumPy and Pandas for data exploration and analysis
  • Learn to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset
Pandas Mastery & Data Frames
Pandas Mastery & Data Frames

Explore the Pandas library fundamentals and learn to create data frames and series. Master the essential tool for data manipulation and analysis in Python.

Data Collection & Selection
Learn systematic approaches to data collection and discover how to select specific data using Pandas. Master data filtering and extraction techniques.
Data Processing Techniques

Master data cleaning, standardization, and normalization processes. Learn to transform messy data into clean, analysis-ready datasets using industry best practices.

Learning Outcomes
Module Summary Duration: 3-4 weeks

By completing this module, you will:

  • Explore the basic understanding of Pandas library – Develop your programming skills with fundamental tools
  • Discover how to use pandas to streamline data cleaning and pre-processing
  • Learn how to create data frames and series in pandas
  • Analyze the process of collecting, cleaning, and pre-processing data
  • Learn how to select data using Pandas
scikit
Machine Learning Fundamentals

Master supervised and unsupervised learning concepts using Scikit-learn. Learn data modeling techniques and discover predictive relationships in datasets through hands-on practice.

Version Control & Development

Learn Git Version Control System (VCS) for managing code and collaborating on projects. Master essential development workflows for data science and machine learning projects.

Model Deployment & WebView
Build and deploy machine learning models using HTML/CSS for web interfaces. Learn to create interactive WebViews to showcase your data science projects.
Learning Outcomes
Module Summary Duration: 4-5 weeks

By completing this module, you will:

  • Learn about training data and how to use datasets to discover potentially predictive relationships
  • Understand basic concepts and common tools used in machine learning
  • Master machine learning techniques, including supervised and unsupervised learning with hands-on modeling
  • Learn the basics of HTML/CSS and Git version control system (VCS)
  • Build and deploy a model to enable WebView functionality
scikit
Unsupervised Learning Mastery
Deep dive into unsupervised learning algorithms including clustering and association techniques. Learn to discover hidden patterns in data without labeled examples.
ML Model Deployment
Master the art of deploying machine learning models into production environments. Learn integration strategies for organizational decision-making processes.
Hybrid Model Development

Learn to innovatively blend supervised and unsupervised models for enhanced performance. Master techniques for tracking and interpreting deployed models.

Learning Outcomes
Specialization Duration: 2-3 weeks

By completing this specialization, you will:

  • Understand the significance of carefully defining the problem before choosing a technique
  • Learn how to get data ready for unsupervised algorithms in particular
  • Explore options for integrating unsupervised models into the organization’s decision-making process
  • Discover how to innovatively blend supervised and unsupervised models for improved performance
  • Learn to interpret and track your unsupervised models for ongoing development

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.

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Student Reviews

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.

Mohammed Ajmal

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!

  • Verified Review

Mohammed Ajmal

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!

  • Verified Review

Mohammed Ajmal

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!

  • Verified Review

Mohammed Ajmal

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!

  • Verified Review

Real-World Capstone Projects

Apply your data science skills to solve real business challenges through hands-on projects. Choose from our curated capstone projects or bring your own organizational problem to create a portfolio that showcases your expertise to future employers.
 

Predictive Analytics Model

Build a machine learning model to address real-world business problems using end-to-end data science processes including data gathering, cleaning, and predictive analysis.
 

Data Visualization Dashboard

Develop comprehensive visual reports and interactive dashboards that transform complex datasets into actionable insights for business decision-making.

 

Exploratory Data Analysis

Create detailed analytical reports that uncover trends, patterns, and anomalies in large datasets from various professional backgrounds and industries.

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 - B&W
Ms. Piyali Mondal Head of Department
Ms. Priti Mondal - B&W
Ms. Priti Mondal Associate Faculty
Dr. Abdullah El Nokiti - B&W
Dr. Abdullah El-Nokiti Professor
Dr. Meraj Inamdar - B&W
Dr. Mohd Merajuddin Inamdar Professor
Dr. Madhavi Vaidya - B&W
Dr. Madhavi Vaidya Professor
Dr. Poonam Chaudhari - B&W
Dr. Poonam Chaudhari Professor
Dr. Anup Maurya - B&W
Dr. Anup Kumar Maurya Professor
Dr. Milan Joshi - B&W
Dr. Milan Amrutkumar Joshi Industry Expert
Dr. Mohamed Elhaw - B&W
Dr. Mohamed Elhaw Industry Expert
Dr. Pradeep Tiwari - B&W
Dr. Pradeep Tiwari Industry Expert
Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our PG Diploma in Data Science and Artificial Intelligence. Learn about program details, requirements, and what to expect from this 6-month certification course.
Why should I join the Data Science program?
Data science combines statistical analysis, machine learning, and business intelligence to solve real-world problems across industries. Our UCAM-certified program provides comprehensive training in Python programming, data analytics, and AI implementation through 200 hours of live instructor-led sessions, preparing you for high-demand roles in the data science field.
What if I fail to attend the classes?
Our blended learning format includes recorded sessions and 24/7 LMS access, allowing you to catch up on missed live classes. You’ll have access to all course materials, assignments, and can schedule additional mentoring sessions with our dedicated student support team to ensure you stay on track.
How does Data Science differ from Big Data and Data Analytics?
Data Science encompasses the entire lifecycle of data – from collection and cleaning to advanced machine learning and AI implementation. While Data Analytics focuses on examining datasets to draw conclusions, Data Science combines programming, statistics, and domain expertise to build predictive models and automated systems.
What can I expect from the Data Science program?
You’ll master Python programming, statistical analysis, machine learning algorithms, and business intelligence tools like PowerBI and Tableau. The program includes 6 assignments, 3 industry-based projects, 6 case studies, and a capstone project, all designed to build a comprehensive portfolio for your career advancement.
Who can join the program?
This course is well suited for participants of all levels of experience because of the high demand for Data Science professionals. It’s beneficial for analytics professionals interested in Python, software and IT professionals interested in Analytics, as well as anyone with a genuine interest in Data Science.

Still have questions?

If you have any other questions or need further information about our Advanced Program in Data Science, don’t hesitate to contact us. Our admissions team is here to help you take the next step in your data science career.

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