I’m ready to commission a complete instructional module aimed at advanced data-science professionals who already speak fluent Python, R, and SQL and want to deepen their expertise. The course must weave together three pillars—Machine Learning Algorithms, Data Visualization Techniques, and Big Data Analytics—into one coherent learning path that challenges seasoned practitioners. Preferred learning experience Video will be the backbone of the program, but I also want complementary assets (readings, interactive notebooks, problem-based labs, short knowledge checks, and a summative capstone) so learners can move seamlessly from concept to application. I’m open to your mix of media as long as it supports a modular structure and keeps the narrative engaging. Scope of work • Map out precise learning objectives for each topic area and align them to Bloom’s higher-order levels. • Produce detailed storyboards, video scripts, slide decks, datasets, and step-by-step lab guides. • Build at least three challenging, real-world case studies that knit the pillars together. • Design auto-graded quizzes and a final project rubric. • Package everything so it can be imported into a standard LMS (SCORM or xAPI preferred). Acceptance criteria The module is considered complete when a pilot group of advanced learners can: 1. Implement and compare multiple ML algorithms on a supplied dataset. 2. Produce interactive visualizations that surface non-trivial insights. 3. Handle a big-data workload (Spark, Hadoop, or similar) and articulate performance trade-offs. If you’ve built graduate-level or enterprise-grade technical courses before, let’s talk about timelines and how you’d approach the storytelling, assessments, and technical depth this audience expects.