Tau oligomers are recognized for their critical role in causing neuronal toxicity and synaptic dysfunction in a diverse array of neurodegenerative diseases collectively referred to as tauopathies. However, the discovery of drugs that specifically target tau oligomers has been impeded by the absence of appropriate screening methods. Here, we suggest a drug screening platform based on tau amyloid corona-shelled nanoparticles (TACONs) to assess the efficacy of tau oligomer-degrading compounds through aggregation-induced colorimetric responses of TACONs. TACONs were engineered via the encapsulation of gold nanoparticles (AuNPs) with homogeneous tau oligomers by leveraging heparin as a co-factor. Our TACON-based strategy harnesses two primary functions of AuNPs: (i) catalytic activators for the selective isolation of tau oligomers and (ii) optical reporters for quantifying colorimetric responses induced by tau oligomer-degrading agents. To validate this approach, we employed proteases that can degrade tau oligomers (protease XIV and plasmin) along with various small molecules known to aid in the treatment of tauopathies. Furthermore, we significantly enhanced screening efficiency by integrating a time-series deep learning architecture, enabling rapid identification of effective compounds within one hour. These results highlight the great potential of deep learning-assisted TACON-based drug screening platform as a powerful strategy for streamlining drug discovery in tauopathies.