The discovery of neutrino oscillations provides the first indication of a lepton flavor violating (LFV) process, one that isn't predicted by the Standard Model. As such, NOvA is part of a rich experimental program to constrain unknown parameters in the neutrino oscillation model, described for three neutrino flavors using the PMNS unitary matrix. It is a long-baseline experiment utilizing two detectors, a Near Detector at Fermilab and a Far Detector in Ash River, Minnesota for a total baseline of $\SI{810}{km}$. It receives a predominantly $\nu_{\mu}$/$\bar{\nu}_{\mu}$ beam peaking at $\SI{1.8}{GeV}$ from the NuMI beam facility at Fermilab. There are four oscillation channels used in the analysis, $\nu_{\mu} \rightarrow \nu_{\mu}$, $\nu_{\mu} \rightarrow \nu_{e}$, $\bar{\nu}_{\mu} \rightarrow \bar{\nu}_{\mu}$ and $\bar{\nu}_{\mu}\rightarrow \bar{\nu}_{e}$. With a total exposure of $13.6\times10^{20}$ and $12.5\times10^{20}$ protons on target for the neutrino and anti-neutrino beam modes respectively, $82$ candidates are seen in the $\nu_{\mu} \rightarrow \nu_{e}$ channel for a total predicted background of $26.8$ events. Similarly, $33$ candidates are seen in the corresponding anti-neutrino channel for a total predicted background of $14.0$ events. In the $\nu_{\mu}\rightarrow\nu_{\mu}$ ($\bar{\nu}_{\mu}\rightarrow\bar{\nu}_{\mu}$) channel, $211$ ($105$) candidates are seen with an expectation of $1156.1$ ($488.1$) events at no oscillations.
Consequently, this dissertation reports a measurement for oscillation parameters based on a joint fit for the spectra in these four channels, which is given by : $\Delta m^{2}_{32} = (2.41\pm 0.07)\times10^{-3}$ eV$^{2}$, $\sin^{2}\theta_{23} = 0.57^{+0.04}_{-0.03}$ (UO) and $\delta_{CP} = 0.82\pi^{+0.27\pi}_{-0.87\pi}$.
In addition, a leading $4.2\sigma$ confidence level of evidence is seen for $\bar{\nu}_{e}$ appearance. The oscillation analysis improves upon previous updates in several areas including particle identification, event reconstruction and cosmic background rejection. A principle component analysis (PCA)-based technique is also implemented for decorrelating important flux and cross-section systematics. In addition, new improvements are proposed in areas of energy estimation as well as confidence interval building.