Professional Certificate in Data Science & DevOps: Unlocking Potential

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The Professional Certificate in Data Science & DevOps is a career-enhancing course that combines the powerful fields of data science and DevOps. This program is designed to equip learners with essential skills demanded by today's top industries, including technology, finance, healthcare, and more.

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In this course, learners explore data science and DevOps fundamentals, machine learning, data visualization, cloud computing, and continuous integration/continuous delivery (CI/CD). Through real-world projects and hands-on labs, students develop a strong understanding of these concepts, preparing them for exciting roles like Data Scientist, DevOps Engineer, and Data Engineer. With the global DevOps market projected to grow to $12.85 billion by 2025, now is the perfect time to upskill and become a sought-after professional in these high-growth areas. Enroll today and unlock your potential for a successful and rewarding career in data science and DevOps!

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โ€ข Unit 1: Introduction to Data Science & DevOps
โ€ข Unit 2: Data Science Fundamentals
โ€ข Unit 3: Data Analysis & Visualization Techniques
โ€ข Unit 4: Machine Learning & Predictive Analytics
โ€ข Unit 5: DevOps Foundations
โ€ข Unit 6: Infrastructure as Code (IaC) with Terraform
โ€ข Unit 7: Continuous Integration & Continuous Deployment (CI/CD)
โ€ข Unit 8: Containerization with Docker & Kubernetes
โ€ข Unit 9: Monitoring & Logging in DevOps
โ€ข Unit 10: Security Best Practices in Data Science & DevOps

่Œไธš้“่ทฏ

In the ever-evolving tech industry, the demand for professionals skilled in Data Science and DevOps continues to grow. This 3D pie chart provides insights into the distribution of roles in this in-demand field. 1. **Data Scientist**: With 30% of the market share, data scientists are highly sought-after professionals who analyze and interpret complex data to help businesses make data-driven decisions. 2. **DevOps Engineer**: DevOps engineers, accounting for 25% of the market, bridge the gap between software development and IT operations, ensuring seamless deployment, monitoring, and scaling of applications. 3. **Data Engineer**: Data engineers, holding 20% of the market, design, build, and maintain data architectures, allowing data scientists and analysts to perform their responsibilities efficiently. 4. **Data Analyst**: Data analysts, representing 15% of the market, collect, process, and perform statistical analyses on data to provide actionable insights for business optimization. 5. **ML Engineer**: Machine learning engineers, with 10% of the market, build and implement machine learning models and algorithms to automate decision-making processes and improve overall business performance. By understanding these roles and their relevance in the industry, aspiring professionals can make informed decisions on which career path to pursue within the Data Science and DevOps realms.

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็คบไพ‹่ฏไนฆ่ƒŒๆ™ฏ
PROFESSIONAL CERTIFICATE IN DATA SCIENCE & DEVOPS: UNLOCKING POTENTIAL
ๆŽˆไบˆ็ป™
ๅญฆไน ่€…ๅง“ๅ
ๅทฒๅฎŒๆˆ่ฏพ็จ‹็š„ไบบ
London School of International Business (LSIB)
ๆŽˆไบˆๆ—ฅๆœŸ
05 May 2025
ๅŒบๅ—้“พID๏ผš s-1-a-2-m-3-p-4-l-5-e
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