In response to the demand for Artificial Intelligence (AI) experts, this study introduced a curriculum development initiative. The aim was to design and implement a Private AI curriculum to understand the computer science (CS) students' evaluations of the curricular activities and their levels of interest and motivation. Twenty-five students, a mix of undergraduates and graduates, were recruited and a scaled-down version of the curriculum was implemented. A parallel mixed-methods approach was employed. The results reinforced the significance of problem-centered curricula in CS context. Students rated the curricular activities highly and demonstrated strong motivation; however, graduates expressed more favorable view of pairwise collaboration and reported higher self-efficacy. Analysis of coding problem-solving behaviors suggested less competent students often relied on trial-and-error, whereas more competent students employed systematic, forward problem-solving strategies. This study contributes to the field of CS by emphasizing the importance of problem-centered learning to prepare students for real-world AI challenges.