Executive Development Programme in Data Science in DevOps Strategy

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The Executive Development Programme in Data Science and DevOps Strategy certificate course is a comprehensive program designed to equip learners with essential skills for career advancement in today's data-driven world. This course is of utmost importance as it bridges the gap between data science and DevOps, two critical areas that are shaping the future of businesses.

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With the increasing demand for professionals who can leverage data to drive business outcomes and implement DevOps strategies, this course offers a unique opportunity to gain expertise in both areas. Learners will develop a deep understanding of data science and machine learning algorithms, as well as DevOps practices such as continuous integration, continuous delivery, and infrastructure as code.Upon completion, learners will be able to design and implement end-to-end data science and DevOps strategies, making them highly valuable to organizations looking to stay competitive in the digital age.

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โ€ข Unit 1: Introduction to Data Science in DevOps
โ€ข Unit 2: Key Concepts in Data Science
โ€ข Unit 3: Data Engineering and Infrastructure in DevOps
โ€ข Unit 4: Data Analysis Tools and Techniques
โ€ข Unit 5: Machine Learning Algorithms and Models
โ€ข Unit 6: Data Visualization and Communication
โ€ข Unit 7: DevOps Practices and Data Science
โ€ข Unit 8: Implementing Data Science in DevOps Workflows
โ€ข Unit 9: Data Security and Privacy in DevOps
โ€ข Unit 10: Building a Data-Driven DevOps Strategy

่Œไธš้“่ทฏ

The above code creates an interactive 3D pie chart showcasing the distribution of roles in the Executive Development Programme in Data Science & DevOps Strategy. The provided statistics represent a snapshot of the industry relevance for each role. 1. **Data Scientist (30%)** Data Scientists are in high demand across industries, with their expertise in leveraging data to generate actionable insights, predictions, and decision-making. 2. **DevOps Engineer (25%)** DevOps Engineers bridge the gap between software development and IT operations, ensuring seamless collaboration, automation, and rapid deployment of applications and services. 3. **Data Engineer (20%)** Data Engineers are responsible for building and maintaining data systems, pipelines, and architecture to ensure data is efficiently and effectively collected, stored, and processed. 4. **Data Analyst (15%)** Data Analysts interpret complex datasets and translate findings into understandable insights, driving business decisions and strategies. 5. **ML Engineer (10%)** ML Engineers focus on building, deploying, and maintaining machine learning models and algorithms, enabling automation, personalization, and predictive analytics in various applications. The 3D pie chart is built using Google Charts, offering a visually engaging and interactive representation of the aforementioned roles. The chart is responsive, adapting to different screen sizes, and has a transparent background with no added background colors. The data table and chart options are defined within the script block, and the google.visualization.arrayToDataTable method is used to create the chart data.

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็คบไพ‹่ฏไนฆ่ƒŒๆ™ฏ
EXECUTIVE DEVELOPMENT PROGRAMME IN DATA SCIENCE IN DEVOPS STRATEGY
ๆŽˆไบˆ็ป™
ๅญฆไน ่€…ๅง“ๅ
ๅทฒๅฎŒๆˆ่ฏพ็จ‹็š„ไบบ
London School of International Business (LSIB)
ๆŽˆไบˆๆ—ฅๆœŸ
05 May 2025
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