Skill Development Workshops Offer By IEEE Bombay Section Year 2019
Introduction
In these workshops students will learn the importance of upcoming technologies such as of Embedded System/ IoT/Machine learning, etc and trends for the future. These workshops are hands-on course especially designs for UG/PG students to develop their hardware and programming skills. These courses will help students to develop their research interest, Proof of Concept (PoC), and prototyping their ideas.
Discipline: Electronics, Telecommunication, Computer Science, Process Control, Automation, etc
Workshop Duration: One or Half Day
Requirements:
- Functional IEEE Students Branch
- Lab with Wifi Facility
Maximum Registration: 40 Students (As per availability of Kits or Computers)
Registration Charges: Rs 300 per IEEE Student Member
Rs: 400 per Non-IEEE Student Member
Program Created and Run by: IEEE Bombay Section
Contact Person: Dr.Saurabh Mehta, TPAC , IEEE Bombay Section
Email Id: saurabh.mehta@vit.edu.in
Note: Please note that workshop speakers traveling and local hospitality expense need to be supported by host institute/college
List of Workshop
| Sr.No. | Workshop Name and Course Content | Trainer | No of Participants | Duration | Requirement from Host |
|---|---|---|---|---|---|
| 1 | Hands-on FPGA, VHDL and Softcore Processor Training -Hands on MAX_10 _Dev Boards Course Content : -Introduction to Programmable Logic: From PALs/PLAs to CPLDs to FPGAs - Software Installation - Introductory Session on VHDL -FPGA Tool Flow and Introduction to Altera Quartus -FPGA Hands-On Session on MAX_10_DEV Boards | Dr.Satyanarayana Bheesette, TIFR & His Team | 20/30 | 1 Day | Computer Lab, Internet Connection, Required Softwares (List will be given in advance by Trainer) Projector, Sound System, etc |
| 2 | Workshop on Embedded System/IoT/Arduino Programming Course Content -Arduino Programming -Sensor Integration -Integrating Communication Module -IoT Applications using Cloud | Dr.Saurabh Mehta, VIT & His Team | 40 | 1 or Half Day | Computer Lab, Internet Connection, Required Softwares (List will be given in advance by Trainer) Projector, Sound System, etc |
| 3 | Machin Learning Workshops 1) Data Analysis with Python (~7 hrs) Python Fundamentals, NumPy, SciPy, Pandas, Pickle, Matplotlib, Seaborn 2) Math for Machine Learning - Linear Algebra and Optimization (~7 hrs) Linear Algebra: Norms, Moore-Penrose Pseudo-Inverse, Special Matrices, Matrix Rank, Eigenvalues and Eigenvectors, Matrix Decompositions (Cholesky, SVD, etc.), Application: Linear Regression Optimization: Gradient Descent, Stochastic Gradient Descent, Application: Linear Regression using GD 3) Math for Machine Learning - Statistics and Probability (~6 hrs) Probability and Statistics concepts useful for Machine Learning, Statistical Hypothesis Testing, Confidence Intervals for evaluation, Application: Anomaly Detection 4) Machine Learning with Python - I (~10 hrs) ML Concepts, Scikit-learn API, Logistic Regression (LR), Model Evaluation, Stochastic Gradient Classifier (SGD), Model Validation, K-Nearest Neighbors (KNN) 5) Machine Learning with Python - II (~10 hrs) Naive Bayes (NB), Support Vector Machines (SVM), Support Vector Regression (SVR), Perceptron, Multi-layer Perceptron (MLP) 6) Machine Learning with Python - III (~10 hrs) Extreme Learning Machine (ELM), Model Comparison with ROC curves, Principal Component Analysis (PCA), t-SNE, K-Means Clustering, Gaussian Mixture Modeling (GMM) 7) Machine Learning Research Topics (~5 hrs) Recommender System, Sentiment Analysis, Eigen-faces | Prof. Santosh Chapaneri, SFIT & His Team | 30/40 | 7 Hrs to 10 Hrs | Computer Lab, Internet Connection, Required Softwares (List will be given in advance by Trainer) Projector, Sound System, etc. |
| 4 | Deep Learning Workshops: (Pre-requisites - Beginner level Python programming skills and conceptual understanding of Machine Learning) 1) Lec: Introduction to Deep Learning (~4 hrs) Understanding of (theory and math) concepts related to DL and CNN 2) Deep Learning for Computer Vision (~7 hrs) TensorFlow & Keras APIs, Multilayer Perceptron using Keras, Deep Multilayer Perceptron using Keras, Convolutional Neural Networks 3) Advanced Deep Learning (~5 hrs) AutoEncoders, Transfer Learning | ||||
| 5 | Workshop on Tinkercad Circuits -Simulation of various boards on tinkercard software -helpful in embedded ckt development | Hannan Satopay | Computer Lab, Internet Connection, Required Softwares (List will be given in advance by Trainer) Projector, Sound System, etc. |
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| 6 | Workshop on Amazon Alexa -How to use Alexa for automation -Handson on developing Alexa skills | Hannan Satopay | Computer Lab, Internet Connection, Required Softwares (List will be given in advance by Trainer) Projector, Sound System, etc. |