This paper summarizes the research in the master thesis entitled "Admission Control and Resource Allocation in 5G Network Slicing". We propose two solutions, SARA and DSARA, based on Reinforcement Learning algorithms to learn the admission policy that optimizes the profit of providers. Resource allocation considers the QoS requirements. Results show the outstanding performance of our solutions to 5G Network Slicing in relation to profit and resource utilization.