IoT |
AI |
Entrepreneurship |
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Sr No | Topic | Details | Sr No | Topic | Details | Sr No | Topic | Details | ||
1
|
Mindset Training |
1 : S/w tools : Git training , digital documentation, OS installation |
1
|
Mindset Training |
1 : S/w tools : Git training , digital documentation, OS installation |
1
|
Mindset Training |
1. S/w tools : Git training , digital documentation | ||
2 : Mindset mapping : Complex thinking , Logical thinking, Learning fast(20hr format), MIT product innovation framework,Newer methods of teaching and colloboration | 2 : Mindset mapping : Complex thinking , Logical thinking, Learning fast(20hr format), MIT product innovation framework,Newer methods of teaching and colloboration | 2. Mindset mapping : MIT product innovation framework,Entreperenuerial mindset training | ||||||||
2
|
Basics of IoT |
1 : C programming upgrade |
2
|
Basics of AI |
1 : Python for AI |
2
|
Understanding Entrepreneurship |
1 : Basic qualities in an entrepreneur | ||
2 : Embedded C | 2 : Numpy and Pandas | 2 : Startup ideationa dn validation | ||||||||
3 : Kernel Style coding | 3 : Machine Learning and DNN basics | 3 : Understanding the lean startup method | ||||||||
4 : Coding standards compliant code (Misra C) | 4 : Introduction to Computer Vision and NLP | 4 : Jugaad and Creativity in Entrepreneurship | ||||||||
5 : Understanding Real world Embedded C code | 5 : Leadership in Entrepreneurship | |||||||||
3
|
Embedded Linux |
1 : Embedded Linux Primer (Bootloader, Kernel,RFS) |
3
|
Insightful Engineer(This modules alignsthe learner withcurrently whatsolutions areavailable in theindustry ) |
Study latest research papers around any AI -CNN application (e.g Face recognition, Pose detection ,Ocr ) |
3
|
Exploring the Startup world |
Understand what goes behind building a startup :- | ||
2 : Device driver writing (Camera) |
– Brief study of available deep learning methods (latest research papers)
– Deep study of top 3 methods – Comparative study of those 3 methods based on defined parameters. – Choose a Problem statement – Implement any one method and try training and tuning for to achieve problem statement goals |
1 : Vision and Validation | ||||||||
3 : Yocto | 2 : Customer Development | |||||||||
4 : Buildroot | 3 : Branding and Design | |||||||||
5 : Router OS (Openwrt) | 4 : Product Development Stages | |||||||||
4
|
Camera |
Image Processing :- |
4
|
Deep Tech |
1 : CNN basics | 5 : Legal and IP | ||||
– Accessing pixels in OpenCV | 2 : Understand each CNN layer in depth | 6 : Go to market strategies | ||||||||
– Splitting color channels | 3 : Building CNN architecture |
4
|
Build an innovative product startup |
1 : Product Design and Development Course | ||||||
– Color maps | 4 : Visualizing each part of CNN | 2 : Market study of existing products | ||||||||
– Color spaces | 5 : Stanford Computer Vision Course | 3 : Analysing skills required to develop the product | ||||||||
– Image manipulation – Pixel change – Grey scale conversion – RGB decomposition – HSV decomposition |
6 : Library tuning | 4 : Forming a team to build the product | ||||||||
– Scaling | 7 : Hyperparameter tuning | |||||||||
– Cropping | 8 : Training Model | |||||||||
– Image filtering | 9 : Testing Model | |||||||||
– Convolutions and cross-correlations |
5
|
AI Product Innovations |
1 : Market study of existing products | |||||||
– Histograms | 2 : Forming a team to build the product | |||||||||
– Linear filters | ||||||||||
– Convolution | ||||||||||
– Co-relation | ||||||||||
Segmentation | ||||||||||
– Thresholding | ||||||||||
– Contours detection | ||||||||||
– Contrours extraction | ||||||||||
– Countours arithmetic | ||||||||||
Feature Detection | ||||||||||
– Edge detection | ||||||||||
– Detecting corners, detecting features | ||||||||||
– Canny edge detector | ||||||||||
Motion and Tracking | ||||||||||
– Tracking in video | ||||||||||
– Optical Flow | ||||||||||
– Tracking using Optical flow | ||||||||||
5
|
IoT Product Innovations |
1 : Market study of existing products | ||||||||
2 : Forming a team to build the product | ||||||||||