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We're here to help you find itCertified Data Science Practitioner (CDSP) Course Overview
The Certified Data Science Practitioner (CDSP) course is a comprehensive training program designed to equip learners with the essential skills and knowledge required to tackle real-world business issues using data science. From initiating and formulating data science projects in Module 1 to effectively communicating results to stakeholders in Module 8, the course covers the full spectrum of data science workflow.
Learners will master the art of Extracting, Transforming, and Loading Data in Module 2, followed by Analyzing Data in Module 3 using various statistical techniques and visualizations. They will then dive into Designing a Machine Learning Approach in Module 4 and further develop specialized skills in Developing Classification Models, Regression Models, and Clustering Models in Modules 5, 6, and 7 respectively.
By the end of the course, participants will be able to deliver end-to-end data science solutions, from Finalizing a Data Science Project to implementing these solutions in a production environment, ensuring they are well-prepared to become proficient data science professionals.
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♱ Excluding VAT/GST
Classroom Training price is on request
♱ Excluding VAT/GST
Classroom Training price is on request
To ensure a successful learning experience in the Certified Data Science Practitioner (CDSP) course, students should meet the following minimum prerequisites:
Please note, while prior experience in data science is not strictly required, a general understanding of the data analytics process will be beneficial. This course is designed to be accessible to those with a foundational skill set and a willingness to learn and engage with the material presented.
The Certified Data Science Practitioner (CDSP) course equips learners with practical skills to solve business problems using data science methodologies.
Target audience for the CDSP course includes:
The Certified Data Science Practitioner (CDSP) course is designed to equip learners with the skills to address business problems through data analytics, machine learning model development, and effective communication of results.