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  • Batch Start Date
    Jan. 27, 2023
  • Number of Students
    20 Seats
  • Learning format
Why join this Programs?
Real World Business

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Learn from Dursikshya Faculty

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Dursikshya's Academic Eminence

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Immense Domain Exposure

learn how ai can be applied across business functions such as Machine Learning.

Express Diploma in AI & Machine Learning

With our highly regarded Fast Track Diploma in AI and Machine Learning, offered in partnership SQA, you may further your career. This program offers the ideal blend of theory, case studies, and significant hands-on application in artificial intelligence instruction.

Key Features
  • 120 hours of training with an instructor
  • Much practice with current features
  • Learn by doing and go through the entire development cycle
  • Advance from basic to intermediate Knowledge of Machine Learning
Tools Covered
Express Diploma in AI & Machine Learning Pathway

  • Basics of Python
  • Data Structures in Python
  • Python Data Processing
  • Utilizing NumPy Arrays
  • Basics of Python Programming

• Overview of Data Science
• Overview of Data Analytics Statistical
• Analysis and Business Applications
• Python Environment Setup and Essentials
• Python for Mathematical Computing (NumPy)
• Python for Scientific Computing (SciPy)
• Pandas Data Manipulation
• Python data visualization using Matplotlib

• Introduction to Machine Learning and Artificial Intelligence
• Preprocessing of Data
• supervised education
• Aspect Engineering
• Classification under supervision
• Unsupervised Education
• Modeling time series
• Collective Learning
• Advisory System

• Introduction to Deep Learning and AI
• Artificial neural networks in lesson two
• Deep Neural Network and Tools 
• Tuning, Optimization, and Interpretability of Deep Neural Networks
• Convolutional Neural Net
• Recurrent neural networks 
• Seventh lesson: Autoencoders

• Learning Objectives
• Required course prerequisites
• Third lesson: RBM and DBNs
• Variational Autoencoder
• Working with Deep Generative Models
• Neural Style Transfer and Object Detection Applications
• Distributed and Parallel Computing for Deep Learning Models
• Reinforcement learning in lesson eight
• Deep Learning Model Deployment and Beyond