05:37
Session 02/09 : 5G Mini Slots & Preemptive Scheduling : For Ultra-Low Latency Use-Cases
06:50
Session 02/08 : 5G Flexible Numerology Explained : Dynamic Subcarrier Spacing SCS in 5G wireless
05:27
Session 02/07 : EN-DC | 5G & LTE Dual Connectivity Explained | Enhanced Coverage & Data Rates
06:29
Session 02/06 : 5G Spectrum Explained: Frequency Bands, Carrier Aggregation, & Bandwidth Parts
11:12
Session 02/05 : | Beamforming & Massive MIMO in 5G | 5G NR Radio Access Network & MIMO Explained
03:56
Session 02/04 : 5G Deployment Options | Standalone vs Non-Standalone Explained
05:42
Session 02/03 : 5G Control Plane & User Plane Separation - CUPS | 5G Architecture Concept
08:59
Session 02/02 : Why We Need 5G | Key Differences Between 4G and 5G Use Cases Explained
09:28
Session 02/01 : 5G Architecture & Key Principles | Complete 5G Network | Course Overview and History
17:49
Practical Exercise 02: Building a Half Subtractor with Xilinx ISE (Ex 02) | VHDL
02:04:20
AI & Machine Learning Fundamentals in 2 Hours for Beginners
02:23:12
Open RAN Fundamentals in 2 hours | ORAN Fundamentals, Deployment, and Innovations | Series : 01
06:31
Session 27: Quick Recap - ORAN Architecture, VNF, NFV, 5G Nodes, and ORAN Deployment
04:49
Session 26 : 5G SA & 5G-NSA Architecture and Deployment strategy and open RAN
05:05
Session 25: Open RAN | New Front Haul eCPRI, Mid Haul and Back Haul Connectivity and new requirement
04:13
Session 24: Open RAN Deployment Scenarios – Regional Cloud vs. Edge Cloud
04:48
Session 23 : Multi-Access Edge Computing (MEC) in Open RAN (ORAN) Explained for Beginners
03:19
Session 22 : SDN (Software-Defined Networking) in Telecom and Open RAN
06:32
Session 21 : NFV (Network Function Virtualization) Concept in Open RAN
04:42
Session 20: Cloudification in Open RAN - The Shift from Traditional to ORAN
09:37
Session 19: Introduction to RIC (Radio Intelligent Controller) in Open RAN and Use Cases
06:32
Session 18: Machine Learning Use Cases in Open RAN
04:09
Session 17: Deployment of Machine Learning Models in Open RAN Networks
05:55
Session 16: Optimizing Open RAN with Machine Learning | concept overview
03:55
Session 15: Explore Unsupervised Learning & Reinforcement Learning for Network Efficiency in openRAN
04:29
Session 14: Introduction to Supervised Machine Learning in Open RAN
04:16
Session 13: Leveraging AI and Machine Learning in Open RAN | Revolutionizing Networks
07:43
Session 12: Exploring RRC Protocol and RRC State Transitions in Open RAN
05:18
Session 11 : Open RAN Protocol Stack | PDCP Protocol and SDAP Layer
04:41
Session 10: Open RAN Protocol Stack | Disaggregation, RLC Protocol, Transmission Modes, MAC Layer
04:01
Session 9: Understanding PUCCH and PUSCH in 5G | Open RAN Explained
05:43
Session 8: Understanding PDCCH, CCE, and Coresets in 5G | Open RAN Fundamentals
04:41
Session 7: Resource Blocks, Frame Structure, and Channel Distribution in RB
07:41
Session 6: Protocol Layers in Open RAN vs. Legacy Networks | Split Layers
05:51
Session 5: Open RAN's Evolution | Legacy to Open RAN Networks
06:28
Session 4: Open RAN Deployment Stages | Legacy to Cloud-Native Networks
10:04
Session 1: Open RAN Basics Explained for Beginners | Introduction and Terminologies
05:44
Session 3: Network Architecture Breakdown | Open RAN vs. Traditional Networks
06:33
Session 2 : Understanding Open RAN: Benefits and Deployment Challenges | ORAN Basics
18:29
Practical Exercise 01 | Step-by-Step: Designing a Half Adder with Xilinx Vivado | VHDL | In Hindi
04:13
Excel Serial Numbering Made Easy: Tips and Tricks
05:12
RFID Reader Setup: Step-by-Step Guide for Windows PC Users | [In HINDI] | Test your RFID reader
06:17
Playlist Premiere | Session 0 : AI/ML Essential Series 1 | High Level overview of AI/ML concept
11:10
Session 18 : Quick Recap | AI/ML Essential | Concept overview for AI/ML Beginners
06:10
Session 17 : Intelligent Decision Agent Idea : Reinforcement Learning Use-Case | Concept overview
05:38
Session 16 : What is Reinforcement Learning | Explained: Key Concepts and Model Breakdown
06:26
Session 15 : What is Dimension Reduction | Explained: A Beginner's Guide for Data Scientists
06:43
Session 14 : Clustering in Machine Learning | The Importance of Clustering in Data Analysis
03:05
Session 13 : What and Why Unsupervised ML: Clustering & Dimension Reduction Basics
05:06
Session 12 : What is Regression Models for Predictions | Core Concept | Overview in Machine Learning
06:01
Session 11 : What is Classification Task in Supervised machine Learning | Beginner-Friendly ML
06:34
Session 10 : Learning AI : Beginners Guide to Supervised Machine Learning | ML Fundamentals
12:10
Session 9 : Aiming for Generalization | Overcoming Underfit and Overfit Models
08:20
Session 8 : Concept of Machine Learning | How Machines Learn: A Simple Explanation | For Beginners
09:41
SESSION 7 : Key Components of ML : Understanding Features, Labels, and Labelled Data in ML!
06:14
Session 6 : Why AI and ML Are Trending | What's Driving the Hype? | AI/ML Today
03:01
Session 5 : AI Explained | What is Applied AI vs. Generalized AI : A Beginner's Guide!
06:23
Session 4 : What is Deep Learning! What You Need to Know About Deep Learning | For Beginners
07:04
Session 3 : What is ML Explained! What You Need to Know About Machine Learning | For Beginners
06:44
Session 2 : What is AI! What You Need to Know About Artificial Intelligence | For Beginners
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