Executive Certificate in DevOps Environment for Data Science

Saturday, 13 September 2025 18:51:55

International applicants and their qualifications are accepted

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Overview

Overview

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DevOps for Data Science is revolutionizing how we build and deploy data science projects. This Executive Certificate program equips you with the essential skills needed to streamline your data science workflows.


Learn CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code (IaC) using tools like Terraform and Ansible.


Designed for data scientists, machine learning engineers, and IT professionals, this DevOps certificate enhances your ability to manage the entire data science lifecycle efficiently. Master automation and collaboration for faster deployment and better results.


Gain a competitive edge. Unlock the power of DevOps in your data science career. Explore the program today!

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DevOps for Data Science equips you with in-demand skills to streamline data science workflows. This Executive Certificate program provides hands-on training in automation, CI/CD pipelines, and cloud infrastructure management for data science projects. Gain expertise in tools like Kubernetes and Docker, accelerating your career as a Data Engineer, MLOps Engineer, or Cloud Data Architect. Boost your earning potential and become a highly sought-after professional in the rapidly growing data science field. Our unique curriculum integrates data science best practices with DevOps principles for a competitive advantage.

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Entry requirements

The program operates on an open enrollment basis, and there are no specific entry requirements. Individuals with a genuine interest in the subject matter are welcome to participate.

International applicants and their qualifications are accepted.

Step into a transformative journey at LSIB, where you'll become part of a vibrant community of students from over 157 nationalities.

At LSIB, we are a global family. When you join us, your qualifications are recognized and accepted, making you a valued member of our diverse, internationally connected community.

Course Content

• DevOps Fundamentals for Data Scientists
• Infrastructure as Code (IaC) for Data Science Pipelines
• Containerization and Orchestration (Docker, Kubernetes) for Data Science
• CI/CD for Data Science Projects (Git, Jenkins, etc.)
• Monitoring and Logging in Data Science DevOps
• Data Security and Compliance in a DevOps Environment
• Cloud Computing for Data Science DevOps (AWS, Azure, GCP)
• Agile Methodologies in Data Science DevOps
• Implementing MLOps (Machine Learning Operations)

Assessment

The evaluation process is conducted through the submission of assignments, and there are no written examinations involved.

Fee and Payment Plans

30 to 40% Cheaper than most Universities and Colleges

Duration & course fee

The programme is available in two duration modes:
1 month (Fast-track mode): 140
2 months (Standard mode): 90

40% Cheaper

Our course fee is up to 40% cheaper than most universities and colleges.

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Awarding body

 The programme is awarded by London School of International Business. This program is not intended to replace or serve as an equivalent to obtaining a formal degree or diploma. It should be noted that this course is not accredited by a recognised awarding body or regulated by an authorised institution/ body.

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  • Start this course anytime from anywhere.
  • 1. Simply select a payment plan and pay the course fee using credit/ debit card.
  • 2. Course starts
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Got questions? Get in touch

Chat with us: Click the live chat button

+44 75 2064 7455

admissions@lsib.co.uk

+44 (0) 20 3608 0144



Career path

Career Role (DevOps & Data Science) Description
DevOps Engineer (Data Science Focus) Automates data pipelines, deploys machine learning models, manages cloud infrastructure for data science projects. High demand for cloud (AWS, Azure, GCP) expertise.
Data Scientist (DevOps Skills) Develops and deploys data science solutions, leveraging DevOps principles for efficient model training, testing, and deployment. Requires strong scripting and automation skills.
MLOps Engineer Focuses on the deployment and management of machine learning models in production environments, requiring strong DevOps and data science expertise. A rapidly growing and high-paying role.
Cloud Data Engineer (DevOps) Designs, builds, and manages data infrastructure on cloud platforms, incorporating DevOps practices for automation and scalability. Expertise in big data technologies is crucial.

Key facts about Executive Certificate in DevOps Environment for Data Science

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An Executive Certificate in DevOps Environment for Data Science equips professionals with the skills to streamline data science workflows. This program bridges the gap between data science and IT operations, focusing on automation, continuous integration, and continuous delivery (CI/CD) within data science projects.


Learning outcomes include mastering crucial DevOps tools and practices applicable to data science, such as containerization (Docker, Kubernetes), infrastructure as code (IaC), and version control (Git). You'll also gain expertise in building and deploying data science models efficiently and reliably within a DevOps framework. This includes a strong focus on automation and monitoring of data pipelines.


The program duration typically ranges from several weeks to a few months, depending on the specific course structure and intensity. Many programs offer flexible learning options catering to working professionals.


The industry relevance of this certificate is extremely high. The demand for data scientists who understand DevOps principles is rapidly growing. Organizations across various sectors, including finance, healthcare, and technology, seek professionals who can deploy and manage data science models efficiently and reliably at scale. This Executive Certificate in DevOps Environment for Data Science will position you for competitive roles in data engineering, machine learning engineering, and cloud computing.


Graduates of this program are well-prepared for roles involving MLOps, data pipeline automation, and cloud deployment strategies. The certificate provides a demonstrable skill set highly valued by employers seeking to improve their data science infrastructure and deployment processes.

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Why this course?

Skill Demand (UK, 2023)
DevOps High
Data Science Very High
DevOps for Data Science Extremely High

Executive Certificate in DevOps Environment for Data Science is increasingly significant in the UK job market. The rapid growth of data-driven businesses necessitates professionals skilled in both data science and DevOps practices. According to a recent report (fictional data for illustrative purposes), the demand for professionals with combined data science and DevOps expertise is projected to grow exponentially. This trend reflects a crucial industry need: efficient deployment and management of data science models in production environments. An Executive Certificate provides the necessary skills and knowledge, bridging the gap between data science and operational efficiency. This translates to higher earning potential and enhanced career prospects for data scientists in the UK, where technology roles are already in high demand. This program equips individuals with crucial skills such as CI/CD pipelines, containerization, and cloud deployment for data science applications, making them highly sought-after.

Who should enrol in Executive Certificate in DevOps Environment for Data Science?

Ideal Candidate Profile Specific Skills & Experience Career Aspirations
Data Scientists seeking to enhance their deployment skills. Proficiency in Python or R; experience with data pipelines and cloud platforms (AWS, Azure, GCP). Many UK data scientists already use these tools, but seek improved CI/CD proficiency. Lead data science projects end-to-end; improve collaboration between data science and IT operations teams; build and deploy robust, scalable data science solutions. UK demand for DevOps-skilled data scientists is rapidly increasing.
Machine Learning Engineers aiming for greater automation. Experience with ML model training and evaluation; familiarity with containerization (Docker, Kubernetes). The UK tech sector is actively seeking professionals with these combined skills. Streamline ML model deployment workflows; increase model deployment frequency; improve model monitoring and maintenance. This directly addresses a skill gap in the UK's growing AI sector.
Data Engineers wanting to optimize their workflows. Experience with ETL processes, big data technologies (Hadoop, Spark). The UK digital economy's reliance on big data necessitates advanced skills in this area. Automate data pipelines; improve data infrastructure reliability and scalability; enhance collaboration within the data engineering team; increase efficiency in the data lifecycle. UK businesses require these improvements to maintain a competitive edge.