Core Viewpoint - Near-infrared spectroscopy (NIR) is a rapidly developing analytical testing technology that offers advantages over traditional methods, such as non-destructive testing, high efficiency, low cost, and minimal sample preparation requirements. However, it requires stable instruments, comprehensive software, and suitable models, making it complex to implement [2][4]. Group 1: Overview of Near-Infrared Spectroscopy - Near-infrared spectroscopy combines spectral measurement in the near-infrared range (800-2500nm) with chemometrics, computer technology, and basic testing techniques for rapid analysis of complex samples. It can determine multiple performance indicators in just a few minutes without sample pre-treatment [2][4]. - The technology is applicable across various fields, including agriculture, pharmaceuticals, petrochemicals, and food, and is considered a modern analytical method with significant potential for agricultural analysis [2][4]. Group 2: Course Introduction - A course titled "Chemometrics and Near-Infrared Spectroscopy" is offered, taught by Professor Shao Xueguang, a recipient of the "Lu Wanzhen Near-Infrared Spectroscopy Science and Technology Award." The course covers foundational knowledge, technical aspects, and algorithms related to NIR spectroscopy [4][9]. - The course aims to alleviate the research burden by providing comprehensive and detailed instruction, addressing key issues such as effective information extraction and model evaluation in quantitative analysis [4][9]. Group 3: Target Audience - The course is designed for technical personnel in industries such as petroleum, chemicals, pharmaceuticals, tobacco, and food, as well as graduate students and researchers in chemistry-related fields [5][4]. Group 4: Course Structure - The course is divided into three main sections: - **Basic Section**: Covers foundational knowledge in chemometrics and NIR spectroscopy, programming basics in MATLAB and Python, and quantitative modeling methods [15][24]. - **Technical Section**: Focuses on modeling processes, including spectral preprocessing, variable selection, clustering, and model transfer, with practical examples [20][24]. - **Algorithm Section**: Discusses common methods such as principal component analysis, partial least squares regression, and neural networks, aiming to enhance understanding and practical application [24][26].

Core Viewpoint - The article emphasizes the importance of seizing the opportunity to enhance skills in the field of chemometrics and near-infrared spectroscopy before the end of the year, positioning it as a critical period for professional advancement [3][4]. Course Highlights - The training program is designed to address common challenges in understanding theory, programming, and practical application, making it suitable for researchers, students, and industry professionals [3]. - The curriculum includes a systematic approach covering foundational principles, technical processes, and advanced algorithms such as principal component analysis and neural networks [7]. - Practical coding sessions in MATLAB and Python will be provided, ensuring a hands-on learning experience that integrates theory with practice [8]. Instructor Profile - The course will be taught by Professor Shao Xueguang from Nankai University, who has extensive experience and achievements in the field of chemometrics [5]. Student Benefits - Participants will gain skills in core algorithms and near-infrared spectroscopy analysis, enabling them to independently handle complex data modeling [12]. - The program supports career advancement in various industries, including pharmaceuticals, environmental science, and food safety, enhancing competitiveness in technical roles [12]. Learning Support - The course offers a dedicated learning platform with on-demand video access, progress tracking by instructors, and a community for peer interaction [13][14]. - A certification will be awarded upon completion, aiding in professional development [15]. Target Audience - The program is aimed at professionals in product development, quality control, and production optimization across industries such as chemicals, food, and pharmaceuticals, as well as students in relevant fields [17]. Enrollment Information - Registration is open from December 1 to December 31, with the course starting on December 31 [19].