One week Microsoft Certification Training on AI Fundamentals

Department of Information Technology organized 1-week Microsoft Certification Training on AI Fundamentals from 24-09-2024 to 30-10-2024 Training Overview The training was conducted over 5 days, with 6 hours of content delivery each day, followed by a certification exam on Day 5. Below is the detailed breakdown of the daily schedule and topics covered: Day 1: Introduction to Machine Learning ? Overview of Machine Learning (ML): ? Types of Machine Learning (Supervised, Unsupervised, and Reinforcement Learning). ? Role of AI in modern applications. ? Algorithms: ? Linear Regression: Predicting continuous outcomes. ? Logistic Regression: Predicting categorical outcomes (binary classification). ? Hands-on Examples: ? Building simple ML models using Python to demonstrate linear and logistic regression. Day 2: Classification and Clustering Techniques ? Decision Trees: ? Tree-based approach for classification. ? Random Forest: ? Ensemble learning for improved model accuracy. ? Support Vector Machines (SVM): ? Optimal hyperplane for classification problems. ? K-Means Clustering: ? Partitioning data into clusters for unsupervised learning tasks. ? Practical Examples: ? Implementation of classification models using Python libraries such as Scikit-Learn. Day 3: NLP and Computer Vision Techniques ? Natural Language Processing (NLP): ? Introduction to tokenization, stemming, and sentiment analysis. ? OpenCV: ? Image processing techniques with OpenCV (e.g., edge detection and face recognition). ? Example Programs: ? Sentiment analysis using Python’s NLTK library. ? Face detection using OpenCV. Day 4: Neural Networks and Deep Learning ? Introduction to Neural Networks: ? How artificial neurons mimic the human brain. ? Types of Neural Networks: ? Convolutional Neural Networks (CNN): Image recognition tasks. ? Recurrent Neural Networks (RNN): Sequential data processing (e.g., time-series forecasting). ? Hands-on Examples: ? Building a CNN for image classification using TensorFlow or PyTorch. ? Implementing RNNs for text prediction.

Start-ups Developed with Linkage of Innovation Ambassadors for Mentorship Support

The Department of IT, in association with Institution’s Innovation Council (IIC), Entrepreneurship Development Cell (EDC) and MREC-HUB, has organized a Poster Presentation on “Start-ups Developed with Linkage of Innovation Ambassadors for Mentorship Support” under IIC Calendar 4.0 Quarter 4 Activity. The event took place at the venue on 27th July 2022 in the presence of Head of The Department (IT) – Prof. Dr. M. Deena Babu, EDC Coordinators, Innovation Ambassadors of all departments and teaching staff. The event was presided and successfully executed by Ms. P Sandhya Priyanka, Asst Prof, EDC & MIC Coordinator – IT. The event gathering was addressed by Dean Academics and then followed by the institute’s IIC and MIC Coordinator.

Microsoft Certification Program On Introduction to Python Programming

Training Schedule: From 27 June to 02 July 2022 Resource Person: Mrs.N.Hemalatha, Managing Director, Skilltimate Technologies, Hyderabad ORGANIZED by: Department of Information Technology Skills Trained: • Perform Operations using Data Types and Operators • Control Flow with Decisions and Loops • Perform Input and Output Operations • Document and Structure Code • Perform Troubleshooting and Error Handling • Perform Operations Using Modules and Tools Finally certificates will be issued to all students those are cleared examination

Deep Learning Algorithms Implementation In Cloud Technology

Introduction to Artificial Intelligence, Machine Learning, Deep Learning and Representation Learning • Machine Learning Mathematics – Linear Algebra, Optimization • Machine Learning Basics – Linear Regression, Perceptron’s, Multilayer Perceptron’s, Stochastic Gradient Descent, Backpropagation • Deep Learning Regularization Techniques: L1, L2, Noise Injection, Data Augmentation, Dropout, Ensemble, Parameter Sharing, etc. • Basics of TensorFlow/ Keras/ PyTorch • CNN Architecture • Object detection RCN and FRCNN • Image Segmentation UNet Model • Computer Vision Applications: Image Classification, Object Recognition and detection using TensorFlow • RNN Architecture and LSTM, Google Colab • Natural Language Processing(NLP) Applications : Machine Translation using TensorFlow/ PyTorch • Current Research – Latest Architectures, Applications

An online Guest lecture on DevOps using Cloud

In This Guest Lecture the Following Topics are Covered: 1. DevOps Model 2. DevOps Working Mechanism 3. Benefits of DevOps 4. Why DevOps Matters 5. How to Adopt a DevOps Model 6. DevOps Real-Time Practices.

Workshop on Internet of Things

Workshop on Internet of Things

FDP on IoT with Raspberry Pi

FDP on IoT with Raspberry Pi

Workshop on Python Programming

Workshop on Python Programming

Industrial Visit to T-HUB

Industrial Visit to T-HUB