Supporting student success in college by identifying and addressing their academic preparedness is one of the biggest challenges facing higher education (Fay et al., 2017; Mokler et al., 2019; National Center for Public Policy and Higher Education & Southern Regional Education Board, 2010). Historically institutions have relied on placement exams for both admission decisions as well as placement into non-credit earning coursework. However, placement tests often generate data that do not accurately portray students' ability levels, which has led to the unnecessary and inappropriate placement of students in remedial courses (Belfield & Crosta, 2012; Scott-Clayton, 2012). In response to the placement exam and remediation debate, the Diagnostic Assessment and Achievement of College Skills was developed (DAACS; Bryer et al, 2024 https://daacs.net). DAACS is a suite of technological and social supports designed to optimize student learning by providing personalized feedback about their strengths and weaknesses in self-regulated learning, writing, mathematics, and reading. Results of a randomized control trial conducted in 2023 showed that students who had access to DAACS in their first semester had a 7.2% higher GPA than the control group (Cohen's d = 0.19). This presentation provides an overview of DAACS and its implementation in the CUNY SPS MS in Data Science program.