>Magister Scientiae - MSc / We are fast moving into an era where data will be the primary driving factor for discovering new unknown astronomical objects and also improving our understanding of the current rare astronomical objects. Wide field survey telescopes such as the Square Kilometer Array (SKA) and Vera C. Rubin observatory will be producing enormous amounts of data over short timescales. The Rubin observatory is expected to record ∼ 15 terabytes of data every night during its ten-year Legacy Survey of Space and Time (LSST), while the SKA will collect ∼100 petabytes of data per day. Fast, automated, and datadriven techniques, such as machine learning, are required to search for anomalies in these enormous datasets, as traditional techniques such as manual inspection will take months to fully exploit such datasets.

>Magister Scientiae - MSc / Future radio surveys as the Square Kilometer Array (SKA) and its precursor, the "Meer" Karoo Array Telescope (MeerKAT), will map the Neutral Hydrogen (HI) in large areas of the sky using the intensity mapping (IM). HI IM is currently one of the most promising ways of accessing the Large-Scale Structure of the Universe. The distribution of matter in the Universe not only encodes its composition but also how it evolves and its initial conditions. An effect on the matter distribution that will be detected by the SKA on the post re-ionization Universe are the Baryonic Acoustic Oscillations (BAO). While it has been shown that in single dish mode the SKA can measure the BAO peak in the radial 21cm power spectrum at low redshifts, this possibility has not yet been studied in detail for the MeerKAT. In this thesis we construct a set of full sky simulations to test how well MeerKAT will be able to extract the BAO wiggles along the line of sight. These simulations are done for the frequencies corresponding to MeerKAT L-band. The maps combine the cosmological HI signal, systematic noise, cosmological foregrounds and the instrumental telescope beam. A model-independent estimator is used to extract the BAO wiggles by subtracting a smooth polynomial component from the 21cm radial power spectrum. We test with simulations if this estimator is biased and the signal to noise of the extraction. We conclude that we are able to remove contaminants and recover the cosmological HI signal while not risking the recovery of the BAO signal. We investigate the effects of varying the sky area and the observational hours on the signal to noise ratio for the BAO wiggles. We found that for a HI IM experiment using MeerKAT, the optimal sky area to detect the BAO along the line of sight is 50% of the sky. With a signal-to-noise ratio of 3.37. This can be achieved with 2000 hours of exposure time