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Certificate in Artificial Intelligence

Course Duration: 3.5 Months

Embark On an Odyssey Through The Digital Mindscape

Discover our Artificial Intelligence course, where imagination meets innovation. Journey into the heart of AI’s algorithms, neural networks, and cognitive computing, uncovering the secrets of machine learning and its endless possibilities. From autonomous vehicles to personalized medicine, explore how AI is revolutionizing every facet of our lives. Engage in hands-on experimentation with state-of-the-art tools and datasets, and delve into the ethical dimensions of AI in society. Whether you’re a visionary technologist, creative thinker, or problem-solving maverick, this course will empower you to shape the future with intelligence and ingenuity.
ICE School offers Diploma in Fashion and Marketing in Nepal

Why Learn AI & ML
In 2024?

By the end of 2024, AI is forecasted to create 2.3 Million jobs, with the highest demand for roles such as AI developers, machine learning engineers & data scientists. Also, according to studies done by the World Economic Forum(WEF), domains such as Artificial Intelligence, Machine Learning, and Data Analytics could create 133 Million new jobs globally. AI and ML in Nepal offer great opportunities for progress and innovation.
  • High Salary
  • High Job Demand
  • Wide Scope of AI & ML in Nepal

Benefits of Our Program

Learn for industry experts
Live classes
Hands on workshops and practical classes
Technical support available in Nepali and English

Technologies Covered
In This Program

Machine Learning
Data Visualization
Deep Learning
Natural language Processing
Date Cleaning
Computer Vision
Artificial Intelligence


In this program, we adopt a case study methodology to disseminate the latest Developments in Cloud Technologies, Deep Learning, NLP and Machine Learning Model Building and its Deployment with the fundamentals of Artificial Intelligence.

Course Structure

Module 1: Artificial Intelligence & Approach
  • Introdution to AI
  • Foundations of the Artificial Intelligence
  • History of Artificial Intelligence
  • State of the art
  • Various Tools and Terminology
  • Application and Scope
Module 2: Computer vision
  • Overview of computer vision
  • Component of computer vision learning
  • Intelligent Agent and Program
  • Constructive computer vision model using AI
Module 3: Introduction to SQL
  • Data Modeling
  • Normalization, and Star Schema
  • ACID transactions
  • DML and DQL Operations
  • Join operations
  • Data Types, Variables and Constants
Module 4: Overview of Robotics in AI
  • Concepts of the Robotic System
  • Different aspects and type of the robots
  • Intelligent Agent and Program
  • Robot Locomotion
  • Components of a Robots
  • Applications of Robotics
Module 5: Implementing AI and LLMs in Business
  • Concepts of LLM
  • Integrate with Business Process
  • Importance of LLM in Business
  • Emerging abilities of LLM in Business
  • Business automation and transformation
Module 6: Initiation to Large Language Model
  • Installation and setup environment
  • Comparative study of LLM model
  • Model selection and implementation
  • Evolution of ChatGPT4 and Bard
  • Customization and build the LLM models
Module 7: AI Ethics & Fairness in LLM
  • Significance of use of ethical AI
  • Ethical Principles and fairness
  • Adverse effect of LLM and AI
  • Various challenges in AI
  • Concepts of Responsible AI
Module 8: Stream Project
  • General Binary Classification (CV)
  • Building and deploying LLM model with Hugging Face
  • NER (Name Entity Recognition)
  • Project
Module 9: ChatGPT and Limitations of AI – I
  • About ChatGPT
  • Significance of ChatGPT
  • Alternatives to ChatGPT
  • Conversational AI and its application
Module 10: ChatGPT and Limitations of AI – II
  • Concepts of Prompting in ChatGPT
  • Human text Generation and its methods
  • Limitations of ChatGPT
  • Application: Researching and Reporting
Module 11: AI Applications: Computer Vision
  • Possibilities of AI in Computer Vision
  • Applications: Medical Imaging, Facial Recognition and Object recognition.
  • Case Study on Robotic Vehicles (Auto driving car )
Module 12: Natural Language Processing
  • Introduction to NLP
  • Significance of NLP and its use
  • Components of NLP
  • NLP Terminology
  • Steps in Natural Language Processing
Module 13: NLP with Neural Network Continued
  • Self Attention Networks: Transformers
  • Introduction to Encoder-Decoder models
  • Encoder-Decoder with RNNs
  • Attention and Beam search
  • Encoder and Decoder with Transformers
  • Transfer Learning through Fine Tuning
Module 14: Neural Networks
  • Artificial Neural Networks
  • Introduction to Encoder-Decoder models
  • Neural Networks and its structures
  • Types of Neural Network
  • Working mechanism of Neural Networks
Module 15: Machine Learning Refresher
  • ML and AI Relationship
  • Predictive Modelling
  • Correlation
  • Types of Neural Network
  • Random Forest & Decision Tree
  • Ordinary least squares (OLS)
Module 16: Machine Learning Continued
  • Classification
  • Logistic regression
  • K Nearest Neighbours (KNN)
  • Clustering
  • Dimensionality reduction methods

Join us for a practical Artificial Intelligence Course that prepares you for a dynamic career in the industry.

Inquire now!