Applied Mathematics and Statistics for Data Analytics
About This Course
Upon successful completion of the module, the trainee will be able to perform the following specific tasks:
• Gain comprehensive understanding of various algorithms and advanced computational methods, foundational mathematical concepts such as linear algebra and vector calculus, and their applications in data science.
•Understand the range, application, and potential pitfalls of various statistical algorithms, and fur-ther deepen the understanding of linear algebra and vector calculus in their context.
• Comprehend the range, application, and potential issues of different data models, and under-stand the role of linear algebra and vector calculus in these models.
• Become proficient in the usage of various analytics platforms and tools, and understand how mathematical concepts like linear algebra and vector calculus are applied within these tools.
• Gain a solid understanding of various statistical modelling techniques and how to apply them us-ing the foundations of linear algebra and vector calculus.
•Master the practical applications of data science, including programming, testing, diagnosing an-alytical models, and using mathematical knowledge of linear algebra and vector calculus.
What You'll Learn
This comprehensive course offers an in-depth exploration of algorithms and advanced computational methods, the application of various statistical algorithms, and different types of data models. It also covers the practical usage of analytics platforms and tools, statistical modelling techniques, and programming languages essential for algorithm and signal design. With a special focus on the mathematical foundations of data science, including linear algebra and vector calculus, the course ensures a robust understanding of the underlying principles that drive data analysis.
The course is not just about theoretical understanding; it places a significant emphasis on practical application. Trainees will learn how to identify appropriate statistical algorithms and data models, use analytics platforms effectively, conduct statistical modelling, and perform coding and configuration based on selected models or algorithms. The course also instills crucial problem-solving skills, enabling trainees to test the effectiveness of models, diagnose unintended outcomes, propose updates, and implement changes.
Upon completion, trainees will be well-equipped to draw relevant trends and insights from data analysis, supporting informed decision-making. This course bridges the gap between theoretical knowledge and practical application, making it an invaluable investment for professionals seeking to elevate their data science skills to the next level. Whether you're a beginner looking to break into the field of data science, or a seasoned professional seeking to stay abreast of the latest developments, "Advanced Data Science: From Theory to Practice" offers the depth and breadth of
Entry Requirements
Diploma with 2 years of working experience.