PG Diploma In Natural Language Processing

45 Credits (ECTS)

PG Diploma In Natural Language Processing

This PG Diploma provides a comprehensive understanding of ML and Deep learning. You'll gain hands-on experience in developing graphical models for lemmatization, synthesising n-gram language models, and conducting comparative analysis. Discover neural networks' capabilities, and unlock practical insights into harnessing neural networks to label POS and NER. Additionally, you'll master the art of training dependency parsers using treebanks and leveraging them to perform diverse NLP tasks.

  • Earn a PG Diploma in Natural Language Processing from Universidad Católica De Murcia, (UCAM) Spain.

  • Universidad Catolica De Murcia (UCAM) Spain, accredited by Ministry of Education, Spain, is a member of Bologna Process in European Higher Education Area (EHEA) and It is also a NARIC-approved and WES-accepted university.

  • It is a 45 ECTS credit programme that offers online learning in conjunction with an industry-leading curriculum.

  • Learners can complete the program within a fixed duration of 9 months.

  • 144 hours of live instructor-led training.

  • 5 industry based projects, 24 assignments, 12 Case Studies.

  • Hands-on experience with the latest tools and applied projects.

  • Live engagement classes by seasoned academics and professionals.

  • Flexible timing for working professionals.

  • Guided Internship and Placement Assistance.

  • Payment Scheme: Monthly Instalments.

Course Module & Fee

Course Registration Fee

$560 (To start with the course)

Monthly Installment

$410 (To be paid on an installment basis for 9 installments)

Total Fee


Admission Requirement

Academic Route

A bachelor’s degree from an accredited university (or academic equivalent) in any subject.

Mature Entry Route


English Language Proficiency Label

If you are not a native speaker, you should have an appropriate English proficiency level, e.g. an IELTS score of 5.5 or equivalent in all bands or possess a bachelor’s degree delivered and assessed in English, or proof of work experience in an English-speaking environment.


Due to its involvement in modern Machine Learning algorithms with math and programming, candidates having knowledge of linear algebra, probability, and calculus could be a plus.

Why UniAthena?


At UniAthena, you are in charge of your learning! You get to decide the pace of your learning based on your financial and time availability. The learning structure is modular, ensuring pace, effectiveness and momentum of your learning journey. With this byte-sized learning format you get to learn anywhere, anytime.


With UniAthena as your learning partner, you follow a ‘Pay as you Go Scheme’ for your program, that means no upfront bulk payment of your fee. Instead, your fee will be divided into small pocket-friendly installments distributed across your program.

Accredited & Globally Accepted

UniAthena has partnered with reputed Universities and Awarding bodies, all of which are fully accredited by governmental regulatory bodies in their respective countries. Universities are NARIC Approved and are part of European Higher education, Bologna process, making the programs recognised worldwide.


Byte-sized learning formats ensure that each learning item carries tangible value in terms of learning outcome, which allows learners to stack or combine small units into higher education credits toward a degree or diploma. At any point of time during your course, you can claim a certificate/diploma based on the credits you have earned so far.



PG Diploma In Natural Language Processing

Awarding Body Accredited By

Ministry of Education, Spain

Fixed Duration

9 Months


Online - Live Classes

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What You Learn

Module 1

Basics of Python

Basics of Python

Duration: 5 weeks

This module discusses the basics of Python programming language and explores how to set up a Python environment to work with machine learning.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 2

Mathematics & Statistics for AI & ML

Mathematics & Statistics for AI & ML

Duration: 5 weeks

This module is designed to help learners to identify the mathematical foundation required for writing programs and algorithms for Artificial Intelligence and Machine Learning.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 3

Python for Machine Learning

Python for Machine Learning

Duration: 5 weeks

The module focuses specifically on Python programming, libraries, and tools needed for data analysis.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 4

Introduction to Machine Learning and Artificial Intelligence

Introduction to Machine Learning and Artificial Intelligence

Duration: 5 weeks

This module provides an in-depth understanding of established methods of artificial intelligence and machine learning techniques.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 5

Advanced Python for NLP (Specialization 1)

Advanced Python for NLP (Specialization 1)

Duration: 5 weeks

This module explores advanced mathematics and discrete optimization to create resilient and high-performance machine learning systems.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 6

Machine Learning for NLP (Specialization 2)

Machine Learning for NLP (Specialization 2)

Duration: 5 weeks

This module aims to examine machine learning models and techniques for Natural Language Processing by applying learning models.

5 weeks

Level: EQF Level 7

Credits: 6 ECTS

Module 7

Capstone Project

Capstone Project

Duration: 2 -3 Months

Bring Your Own Project Learn to solve a problem that you/your organization is facing using Natural Language Processing.

2 -3 Months

Level: EQF Level 7

Credits: 9 ECTS


Students would Recommend this Course 


Students Observed Improvement in Performance at Work 

Partners of this Programme

Universidad Católica De Murcia (UCAM) is a university par excellence based out of Murcia, Spain. Established in 1996, the university is accredited by the Ministry of Education, Spain, ANECA, and is a member of ENQA, Universia, and EUA. UCAM is ranked among the 200 best universities in Europe and the 10 best valued by its students by The Times Higher Education World University Rankings 2021. UCAM has a strategic partnership network with more than 280 universities.

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Admission Process

Please find below the detailed steps to be followed as a part of the admission process.

Why This Course ?

Course Resources

For more detailed information about the course, please click on the link/links below.

Why This Course ?


Domain Expertise

The course facilitates a wide range of skills to help learners deepen their domain knowledge in Natural Language Processing. It will allow them to master skills including Machine Translation, Sentiment Analysis, Transformers, Local-Sensitive humming, Vector space models, Attention models, and more.


Wide-ranging Curriculum

The programme’s broad curriculum aims to equip learners with a solid foundation in key areas underpinning the field of Natural Language Processing including Basics of Python, Mathematics & Statistics for AI & ML, Python for Machine Learning, Introduction to Machine Learning and Artificial Intelligence, Advanced Python and Machine Learning for NLP.


Real-world Applications

The course incorporates a comprehensive suite of frameworks, including Scripting Tools, IDE shells, Database Integrations, Data Analytics Libraries and Machine Learning models.

How You Learn ?

Scientifically developed learning pedagogy, which ensures quality and effective learning experience for the learners. We ensure a seamless learning experience for students with varying levels of expertise on the subject matter.

What You Receive ?

You will be receiving the following certificates as specified below:


PG Diploma In Natural Language Processing issued by

Universidad Catolica De Murcia (UCAM), Spain

All certificate and transcript images are for illustrative purposes only and may be subject to change at the discretion of respective Universities or Awarding Bodies.

Ready to Start ?

Getting started with us is incredibly easy. All you need to do is register for this course with minimal details and you'll be ready to go.

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Frequently Asked Questions

1. Professionals who have a keen interest in AI.
2. Career starters interested in the field of AI.
3. Students aiming for their career in AI and Machine Learning.
4. Software and IT Professionals.
5. Individuals and professions looking for a career change.
6. Engineers, Marketing, Healthcare, and Finance Professionals aiming for career excellence.

Applicants should have a Bachelor’s degree or equivalent qualification in order to be eligible for this course. Additionally, applicants must have adequate proficiency in the English language.

Due to its involvement in modern Machine Learning algorithms with math and programming, candidates having knowledge of linear algebra, probability, and calculus could be a plus.

All applicants are required to upload the following documents in order to be eligible for admission:

1. Bachelor's Degree Certificate (Official translations should be submitted if the documents are not in English).
2. The final transcript of the Bachelor's Degree.
3. A copy of the government-issued photo identity.

The core resources of the program are video classes and related reading materials. The learners will get Live Virtual training and also on-demand learning support.

We provide on-demand learning support to every student and every student receives pastoral support and guidance from in-house student engagement team.

This program does not involve written examinations. Upon enrolling, your performance will be evaluated based on the outcomes of your capstone projects and assignments. Be informed that a final submission will encompass both the project and assignment aspects. To ensure successful completion, kindly adhere to the specified deadline for submitting assignments and capstone projects within each unit.

The following are the Application and Use Cases of this Course:

1. Clinical Documentation
2. Checking Grammar
3. Search Autocorrect and Autocomplete
4. Business Analytics
5. Document Classification
6. Text Summarization
7. Automated Speech/Voice Recognition

The skills covered during the program are:

- Word2vec
- Machine Translation
- Sentiment Analysis
- Transformers
- Attention Models
- Word Embeddings
- Locality-Sensitive Hashing
- Vector Space Models
- Parts-of-Speech Tagging
- N-gram Language Models
- Autocorrect

Once you have registered for the course, you can complete the programme in a fixed time period of 9 months.

Each module must be completed within 5 weeks of the enrollment date.

This Diploma is certified by Universidad Católica de Murcia (UCAM), Spain, accredited by ANECA (National Agency for Quality Assessment and Accreditation of Spain) and the Ministry of Education regarding 17 of its undergraduate degrees.

Under any unforeseen circumstances, if you want to withdraw from the programme, you may be unable to apply for an Early Exit Award.

There will be a formal convocation ceremony conducted by UCAM in UAE.