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PG Diploma in Artificial Intelligence and Machine Learning
The AI-ML program covers essential topics like Statistics, Machine Learning, Deep Learning, Natural Language Processing, and Reinforcement Learning. Live sessions by global practitioners, labs, and industry projects are all incorporated into this program through our interactive learning model. Aims at acquiring industry-valued skills and the most commonly used tools and techniques.
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Application deadline : May 29

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Batch starts date

June 26, 2023

Program Duration

9 Months

Learning Format

Blended Learning

Program Fees

$4250

Course Overview

Artificial Intelligence course is designed for C-suite leaders and founders who are looking for ways to set their business up for future success., and who want to use the power of EI to improve AI outputs in their organizations. Digital experts who want to get more out of their existing AI outputs also stand to benefit greatly from the course. This course covers understanding extended intelligence and to apply Big Data and AI techniques to business scenarios. Also focuses on actionable frameworks for creating human-compatible AI systems.

Training Key Features

  • 144 hours of live instructor-led training
  • 5 industry based projects, 24 assignments, 12 Case Studies
  • 24/7 support and LMS Access
  • Hands on experience with latest tools and applie projects
  • Live engagement classes by seasoned academics and professionals
  • 3 guaranteed interviews by Airtics
  • Flexible timing for working professionals
  • EMI option
  • Internship and placement

For More Information

    What you will learn

    • Build ML models with NumPy & Scikit-learn, Build & train supervised models for prediction &binary classification tasks (linear, logistics regression)
    • Build & train neural networks with TensorFlow to perform multi-class classification & build & use decision trees & tree ensemble methods.
    • Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including & anomaly detection.

    About UCAM

    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.

    Airtics Education’s PG Diploma Programs are certified by UCAM University.

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    Skills Covered

    Machine Learning

    Deep Learning

    Natural Language processing

    Reinforcement Learning

    Computer Vision

    Neural Networks

    Who Can Apply for the Course?

    • Professionals who have keen interest in AI
    • Career starters interested in the field of AI
    • Students aiming their career in AI and Machine learning
    • Software and IT Professionals
    • Individuals and professions looking for a career change
    • Engineers, Marketing, Healthcare, Finance professionals aiming for career excellence.

    Tools/ Frameworks/ Libraries

    Scripting tools

    Python, R

    Tools/Libraries

    Pandas, numPy, seaborn, matploltlib, cufflinks, scikit, NLTK, CoreNLP, spaCy, PyNLP, Flask

    IDE shell

    Jupyter Notebook, google colab, pycharm, visualstudio code

    Automated Machine Learning Models

    Supervised, Unsupervised, Reinforced learnings

    Application And Use Cases

    Financial trading
    Marketing personalization
    Recommendations
    Online search
    NLP-Natural language preprocessing
    Recommendations
    Predictive analytics
    Forecasting trends

    Eligibility

    Firm Knowledge Of Software Fundamentals With Data Structures, Linear Programming And Architecture Is Beneficial. Candidates From Programming And Non-Programming Background Could Also Opt For This In-Demand Course.

    Prerequisites

    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.

    Course Modules

    Module 1
    Module 2
    Module 3
    Module 4
    Specialization Module 1
    Specialization Module 2
    OR
    Specialization Module 1
    Specialization Module 2
    • Python basics
      • Variable and data types
      • Conditional statements
      • Loops
      • Functions
    Python Libraries
    • Numpy
    • Pandas
    • matplotlib
    LEARNING OUTCOMES
    • Learning python structure and how to write programs in it.
    • Basic concepts of Python, its syntax, functions, and conditional statements.
    • Acquire the prerequisite Python skills to move into specific branches – Machine Learning, and Data Science.
    • Understand packages to enable them to write scripts for data manipulation and analysis.
    • Linear algebra
    • Probability
    • Statistics
    • Statistical tools
      • CSV
      • Excel
    LEARNING OUTCOMES
    • Introduce statistical tools for working with datasets
    • 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.
    • Learning to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.
    • Analysis library
      • Pandas
    • Data Collection
    • Data Cleaning and pre-processing
    • Data Frames
    • Standardization
    • Normalization
    LEARNING OUTCOMES
    • 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
    • Analyse the process of collecting, cleaning, and pre-processing data
    • Learn how to select data using Pandas
    • Introduction to machine learning
    • Supervised Learning
    • Unsupervised learning
    • ML Deployment
    LEARNING OUTCOMES
    • You will learn about training data, and how to use a set of data to discover potentially predictive relationships.
    • Understand basic concepts and common tools used in machine learning.
    • you will master machine learning techniques, including supervised and unsupervised learning and hands-on modelling, rounding out your artificial intelligence education.
    • learn popular machine learning algorithms, Feature Selection, and Mathematical intuition behind it.
    • Learn the basics of HTML/CSS, and Git version control system (VCS).
    • Build and Deploy a model to enable WebView.
    • Core Python for computer vision
      • Strings
      • Regex
    • Machine Learning algorithms
      • Regression
      • KNN
      • SVM
    • Computer vision tools
      • Keras
      • TensorFlow
    LEARNING OUTCOMES
    • Revising python structure and how to write programs in it.
    • Hands-on Python Strings, Regex.
    • Acquire the prerequisite Python skills to move into specific branches – Natural Language Processing.
    • Understand NLP python packages to enable them to write scripts for text pre-processing.
    • learn popular machine learning algorithms, Feature Selection, and Mathematical intuition behind it.
    • Understand basic concepts and common tools used in NLP.
    • Artificial Neural Networks
    • Text Processing
    • Text classification
    • Topic Modelling
    • Recurrent neural networks
    LEARNING OUTCOMES
    • Concepts of deep learning to build artificial neural networks and traverse layers of data abstraction and get a solid understanding of deep learning using TensorFlow and Keras.
    • Understanding text processing and vectorization for ML Use case.
    • Develop and build fully automated NLP algorithms in burt and transformers.
    • Evaluation of various NLP Algorithms.
    • Understand the concepts of NLP, feature engineering, natural language generation, automated speech recognition, speech-to-text conversion, text to speech conversion.
    • Gain insights about advancements in NLP, AI and Machine Learning techniques.
    • Core Python for computer vision
      • Strings
      • Regex
    • Machine Learning algorithms
      • Regression
      • KNN
      • SVM
    • Computer vision tools
      • Keras
      • TensorFlow
    LEARNING OUTCOMES
    • Revising python structure and how to write programs in it.
    • hands-on Python Strings, Regex.
    • Acquire the prerequisite Python skills to move into specific branches – computer vision.
    • Understand image processing python packages to enable them to write scripts for text pre-processing.
    • learn popular machine learning algorithms, Feature Selection, and Mathematical intuition behind it.
    • Understand basic concepts and common tools used in computer vision.
    • Artificial Neural Networks
    • Image Processing and OpenCV
    • Convolutional Neural Networks
    • Object Detection Technique
    LEARNING OUTCOMES
    • Concepts of deep learning to build artificial neural networks and traverse layers of data abstraction and get a solid understanding of deep learning using TensorFlow and Keras.
    • concepts of computer vision, feature engineering, object detection, object tracking.
    • Develop and build fully automated CV algorithms USING YOLO.
    • Evaluation of various CV Algorithms.
    • Develop and build fully automated vision systems.
    • Gain insights about advancements in CV, AI, and Machine Learning techniques.

    Interested in This Program? Secure your spot now.

    The application is free and takes only 5 minutes to complete.

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      Student Reviews

      Veeraiah Yadav Doddaka
      IT Manager, Samsung

      I choose to learn Data Science and explored many options on which institute to join, among that what I found is Airtics as the best in terms of the course curriculum/on line content they designed and most…..

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      Prasad Joshi
      RF Optimization Engineer, Nokia

      I was a Data Science student at Airtics Education, which helped build a solid data science background and sharpen my programming skills…

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      Mohamed Hanan
      Procurement Assistant

      The program in Data Science offered by Airtics Education is rigorous and has provided me with a greater understanding of the data science world…

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      Capstone Projects

      House rental Prediction

      Image Classification

      Business insights reporting

      Career Support

      Frequently Asked Questions

      With the pace that every industry is introducing Artificial intelligence in their domain, Learning this course will open up a world of opportunities to create point and innovative technologies in diverse sectors.

      We provide you live recorded classes of the same session to follow up if you end up missing the same.

      Data science and machine learning are a subset of artificial intelligence. The purpose of data science and ml is to reach to the point of AI. That the machine should start thinking or make decisions like a human being. AI requires a continuous feed of data to learn and improve decision-making

      Accelerated Artificial intelligence career guidance with world-class training on the most in-demand Data science and Machine learning skills. Training and hands-on experience with key tools and technologies including Python, PowerBi and concepts of Machine Learning, statistics, natural language preprocessing, deep learning, computer vision and more.

      Aspirants and professionals who have basic computer programming skills can enroll in the course.
      Basic knowledge of programming logic and technology exposure will be helpful.
      For Machine learning, you should be good at Linear Algebra, Multivariate Calculus, Probability, and Statistics.
      Python is in the first place, especially for beginners. But if you are well versed in Machine Learning, then you can learn the R Programming language.

      Big NO! In machine learning, you need to build a machine learning model. And to build a model, you should know programming.

      What is included in this course?

      • Live Training from Experts
      • Industry based projects
      • Curriculum designed by industry experts
      • Internships & Guaranteed interviews
      • Internationally valued certification

      I’m Interested in This Program

        By providing your contact details, you agree to our Terms of Use & Privacy Policy

        Contact Us

        Airtics Education
        703, City Gate Tower
        Al Ittihad Road, Al Taawun
        Sharjah,UAE

        info@airtics.org

        +971 6 745 2556

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          Course Preview

          PG Diploma in Artificial Intelligence and Machine Learning


            By providing your contact details, you agree to our Terms of Use & Privacy Policy