COURSE OUTLINE: In order to understand natural phenomena like phase transitions or nucleation or many biological reactions like protein folding, enzyme kinetics, we need to understand how many particles interact and behave together in a certain specified manner. For example, ice melts at 00 C and water boils at 1000 C, at low temperature the raindrops form in the upper atmosphere. Enzyme beta-galactosidase allows the breaking of the C-O bond that leads to the digestion of lactose . These are complex processes that involve many particles to behave in a collective fashion. This could happen because of the interaction among particles. However, these cannot be solved by Newton’s equations, because we cannot solve Newton’s equations even for three particles interacting system. So the forefathers of this field, Maxwell, Boltzmann and Gibbs introduced the probabilistic approach and combined it with mechanics to form the ‘Statistical Mechanics.’ This a branch of theoretical science that parallels Quantum Mechanics and these two together form the main tools at our disposal to understand why things happen and how they happen. The present course will address the basic postulates of Statistical Mechanics and then will show how starting from the basic postulates one builds a formidable framework that can be used to explain phenomena mentioned above.