Network coding is a novel research area that enhances the efficiency and robustness of communication networks. Unlike traditional packet forwarding, network coding allows intermediate nodes to send packets that are linear combinations of previously received information. This approach offers two main benefits: improved throughput and enhanced robustness, particularly in environments with partial or uncertain information. The paper provides an introduction to network coding, explaining its mechanisms, theoretical foundations, and practical applications. Key concepts include linear network coding, where packets are combined using linear operations over a finite field, and the use of encoding vectors to facilitate decoding. Network coding can be implemented deterministically or randomly, with the latter being more flexible but potentially less efficient. Practical considerations such as decoding, packet generation, delay, and finite field operations are also discussed. The paper highlights the benefits of network coding in static and dynamic environments, including increased capacity for multicast flows, improved robustness, and adaptability. It demonstrates how network coding can achieve optimal throughput in decentralized algorithms and improve performance in packet erasure networks. Several applications of network coding are explored, including P2P file distribution, wireless networks, ad-hoc sensor networks, and network tomography. These applications leverage the advantages of network coding to enhance performance, reduce overhead, and improve security. The paper concludes by emphasizing the potential of network coding in designing new networking and information dissemination protocols, particularly in emerging areas like ad-hoc networks and sensor networks.Network coding is a novel research area that enhances the efficiency and robustness of communication networks. Unlike traditional packet forwarding, network coding allows intermediate nodes to send packets that are linear combinations of previously received information. This approach offers two main benefits: improved throughput and enhanced robustness, particularly in environments with partial or uncertain information. The paper provides an introduction to network coding, explaining its mechanisms, theoretical foundations, and practical applications. Key concepts include linear network coding, where packets are combined using linear operations over a finite field, and the use of encoding vectors to facilitate decoding. Network coding can be implemented deterministically or randomly, with the latter being more flexible but potentially less efficient. Practical considerations such as decoding, packet generation, delay, and finite field operations are also discussed. The paper highlights the benefits of network coding in static and dynamic environments, including increased capacity for multicast flows, improved robustness, and adaptability. It demonstrates how network coding can achieve optimal throughput in decentralized algorithms and improve performance in packet erasure networks. Several applications of network coding are explored, including P2P file distribution, wireless networks, ad-hoc sensor networks, and network tomography. These applications leverage the advantages of network coding to enhance performance, reduce overhead, and improve security. The paper concludes by emphasizing the potential of network coding in designing new networking and information dissemination protocols, particularly in emerging areas like ad-hoc networks and sensor networks.