OMACS Sandbox for Current Digital Age

Explore wireless communication concepts through 12 experiments, Starting from understanding AWGN and Fading channel generation, its impact on Transmitted symbols, BER analysis, path loss, Doppler effects, OFDM, to channel capacity in SISO, MISO, SIMO, &MIMO systems. Gain practical insights into by visualizing and algorithm design using python programming.

Ref:
1. wireless communications by Andrea Goldsmith.
2. Fundamentals of wireless communication by David Tse.
3. Wireless communication by Rappaport.

Note: For Instructions: Must Watch Introduction Video and Must follow at Announcements for more instructions

Explore the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML) through core concepts, algorithms. Understand the differences between AI, ML, and Deep Learning while diving into key topics such as supervised and unsupervised learning, classification, regression, clustering. Learn about model training, evaluation, and optimization techniques. Gain hands-on experience by implementing AI/ML algorithms using Python, enabling practical insights into data-driven decision-making and intelligent systems.

Ref:
1. Grokking Machine Learning by Luis G. Serrano, Manning Publications ,
2. Intro to Machine Learning by Kilian Q. Weinberger, Cornell University,
web: https://www.cs.cornell.edu/courses/cs4780/2024sp/

Note:
For Instructions: Must Watch Introduction Video and Must follow at Announcements for more instructions

Explore the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML) through core concepts, algorithms. Understand the differences between AI, ML, and Deep Learning while diving into key topics such as supervised and unsupervised learning, classification, regression, clustering. Learn about model training, evaluation, and optimization techniques. Gain hands-on experience by implementing AI/ML algorithms using Python, enabling practical insights into data-driven decision-making and intelligent systems.

Ref:
1. Grokking Machine Learning by Luis G. Serrano, Manning Publications ,
2. Intro to Machine Learning by Kilian Q. Weinberger, Cornell University,
web: https://www.cs.cornell.edu/courses/cs4780/2024sp/

Note:
For Instructions: Must Watch Introduction Video and Must follow at Announcements for more instructions

Explore fundamental signal processing concepts through 18 experiments, starting from generating continuous and discrete time signals, performing mathematical operations, and analyzing their properties. Understand signal decomposition, sampling effects, convolution, and spectral representations through Fourier and Laplace transforms. Delve into system analysis using pole-zero representation, Z-Transform, DTFT, and power-energy computations. Gain practical insights by visualizing and designing algorithms using Python programming.