Executive Certificate in DevOps Automation for Data Science

Sunday, 14 September 2025 03:59:23

International applicants and their qualifications are accepted

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Overview

Overview

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DevOps Automation for Data Science is an executive certificate designed for data scientists and IT professionals.


It bridges the gap between data science and IT operations.


Learn CI/CD pipelines and automation tools like Jenkins and Ansible.


Master containerization with Docker and orchestration with Kubernetes.


This DevOps Automation for Data Science certificate enhances your skills in cloud computing and infrastructure management.


DevOps practices optimize your data science workflows for faster delivery and improved efficiency.


Gain a competitive edge in the rapidly evolving data science landscape. Enroll today and transform your career!

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DevOps Automation for Data Science: This executive certificate program accelerates your data science career by mastering essential automation skills. Learn to streamline workflows using CI/CD pipelines, infrastructure as code (IaC), and containerization technologies like Docker and Kubernetes. Gain hands-on experience with cloud platforms like AWS and Azure. This DevOps program boosts your marketability, opening doors to high-demand roles in data engineering and cloud computing. Enhance your efficiency and deploy data science projects faster and more reliably. Our unique blend of theoretical knowledge and practical projects ensures you're job-ready upon completion. Accelerate your DevOps journey today!

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

• **Introduction to DevOps Principles for Data Science:** This foundational unit covers core DevOps concepts and their application within a data science context, including Agile methodologies and CI/CD pipelines.
• **Infrastructure as Code (IaC) for Data Science:** Learn to manage and provision infrastructure using tools like Terraform and CloudFormation, focusing on data science workloads and resource optimization.
• **Containerization and Orchestration (Docker & Kubernetes):** Master containerization best practices for data science applications, deploying and managing them efficiently using Kubernetes.
• **DevOps Automation for Data Science Pipelines:** This unit delves into automating data ingestion, processing, model training, and deployment using tools like Jenkins, Airflow, and Git.
• **Monitoring and Logging for Data Science Applications:** Implement robust monitoring and logging strategies to ensure the reliability and performance of data science systems, covering tools like Prometheus and Grafana.
• **Security in DevOps for Data Science:** Focuses on securing data science infrastructure and workflows, addressing topics like access control, data encryption, and vulnerability management.
• **Cloud Platforms for DevOps and Data Science (AWS/Azure/GCP):** Explore cloud-based DevOps practices and tools specific to major cloud providers, with hands-on experience in at least one platform.
• **DevOps Automation Best Practices and Collaboration:** This unit covers collaboration techniques, efficient workflows, and best practices for implementing successful DevOps strategies in a data science team.

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, manages cloud infrastructure, and ensures seamless data flow for data science projects. High demand for CI/CD expertise.
Data Scientist (with DevOps Skills) Develops and deploys machine learning models, leveraging DevOps practices for efficient model versioning and deployment. Strong automation skills are key.
MLOps Engineer Focuses on the deployment and management of machine learning models in production environments. A specialist role requiring both data science and DevOps skills.
Cloud Data Engineer (DevOps) Designs, builds, and manages data infrastructure on cloud platforms, applying DevOps principles for automation and scalability. Experience with automation tools crucial.

Key facts about Executive Certificate in DevOps Automation for Data Science

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An Executive Certificate in DevOps Automation for Data Science equips professionals with the skills to streamline data science workflows, significantly boosting efficiency and productivity. This program focuses on automating repetitive tasks, improving collaboration, and accelerating deployment of data science models.


Learners will gain proficiency in automating various stages of the data science lifecycle, including data ingestion, preprocessing, model training, and deployment. Key skills acquired include using CI/CD pipelines, containerization (Docker, Kubernetes), infrastructure as code (IaC), and configuration management tools relevant to data science projects. Cloud platforms like AWS, Azure, or GCP are often integrated into the curriculum for practical experience.


The program's duration typically ranges from several weeks to a few months, depending on the intensity and curriculum design. Many programs are structured to allow flexible learning, accommodating busy professionals' schedules with online or blended learning options.


Industry relevance is paramount. This DevOps Automation for Data Science certificate directly addresses the growing need for data scientists to collaborate effectively with IT operations and to deploy models rapidly and reliably. Graduates are well-prepared for roles requiring automation expertise, such as DevOps Engineers, Data Engineers, Machine Learning Engineers, and Data Scientists seeking to enhance their operational skills. MLOps practices are a significant component, improving the entire machine learning lifecycle.


In short, this certificate provides practical, in-demand skills, resulting in improved career prospects and higher earning potential within the data science and technology sectors. The focus on automation and cloud technologies ensures graduates are equipped to handle the complexities of modern data science deployments.

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Why this course?

An Executive Certificate in DevOps Automation for Data Science is increasingly significant in today's UK market. The demand for data scientists proficient in DevOps practices is soaring. According to a recent survey (hypothetical data for illustrative purposes), 70% of UK tech companies report a skills gap in this area, highlighting a significant opportunity for professionals seeking career advancement. This certificate bridges this gap by equipping learners with the necessary skills to automate data science workflows, improving efficiency and deployment speed. The ability to implement CI/CD pipelines for data science projects is highly sought after, leading to improved collaboration between data scientists and IT operations.

Skill Demand (%)
DevOps Automation 70
Cloud Computing 65
Data Visualization 55

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

Ideal Candidate Profile Skills & Experience Career Goals
Data scientists, machine learning engineers, and data analysts seeking to improve efficiency and scalability of their data pipelines through DevOps automation techniques. Proficiency in programming languages like Python or R, experience with data processing frameworks (e.g., Spark), and familiarity with cloud platforms (AWS, Azure, GCP). (Note: According to recent UK government data, the demand for data professionals with cloud skills is rapidly increasing.) Advance their careers by gaining in-demand skills in DevOps automation for data science, leading to roles with higher salaries and responsibilities. Mastering CI/CD pipelines and infrastructure-as-code will enhance their overall project management.
IT professionals with a background in DevOps who want to specialize in data science workflows. Experience with automation tools such as Jenkins, Ansible, or Terraform, and a strong understanding of Linux and containerization technologies (Docker, Kubernetes). Transition into data-focused roles by bridging their DevOps expertise with data science practices. They will become highly sought-after professionals specializing in streamlining data pipelines.