MLOps Training in Hyderabad
With
Certification & 100% Placement Assistance
Classroom course | Online course | Capstone Projects | 3–4 Months | Flexible EMI | Free Demo Class
Looking for the best MLOps Training Course in Hyderabad? Our certification program covers MLOps fundamentals, end-to-end ML lifecycle management, CI/CD pipelines, cloud ML platforms, model deployment, monitoring, and industry best practices. Learn hands-on with capstone projects based on real-world machine learning data, a placement-focused curriculum, and use cases relevant to Hyderabad's IT market. With 100+ hours of expert-led sessions, flexible weekday/weekend batches, online/offline modes, and dedicated placement assistance, this course positions you for a successful career as an MLOps engineer, ML engineer, or AI/DevOps professional.
MLOPS Training in Hyderabad
Next Batch Details
| Trainer Name | Dr. Raju |
| Trainer Experience | 13+ Years |
| Next Batch Date | 22nd Sept (Offline), 15th Sept (Online) |
| Training Modes: | Online and Offline Training (Instructor-Led) |
| Course Duration: | 3 Months (Offline & Online) |
| Call us at: | +91 81868 44555 |
| Email Us at: | brollyacademy@gmail.com |
| Demo Class Details: | ENROLL FOR FREE DEMO CLASS |
Why Brolly Academy is the Best MLOps Training Institute in Hyderabad
12+ Years
Leading MLOPS & Machine Learning Operations training
300+ Reviews
Praised by students for placement support and hands-on learning
4.8 Rating
Top-rated MLOPS training institute on Google
4,500+ Students
Across MLOPS, AI, and Data Engineering programs
3 Months
Duration
Modes
Multiple Modes Online, Offline & Hybrid learning options
Fee Range
Affordable Fees With EMI plans & free demo sessions
20+ Capstone Projects
Real-time MLOps projects on MLflow, Kubeflow, Azure ML, AWS Sage maker
Why Choose Brolly Academy for MLOps Training in Hyderabad?
- Industry-ready MLOps curriculum, job-focused
- Trainers with 13+ years’ real MLOps and cloud experience
- Live & recorded classes, unlimited lifetime access
- Learn MLflow, Kubeflow, Docker, Kubernetes, Azure ML, AWS Sagemaker
- Advanced Python, CI/CD, cloud deployment, practical implementation focus
- Flexible learning: classroom, online, hybrid program
- Personalised mentorship, career guidance, and support
- One-on-one placement, dedicated career mentorship
- 100% placement support, including job referrals
- Capstone projects, production ML pipelines, and real cloud data
- Affordable fees, simple EMI payment plan available
- 3-month advanced training, in-depth MLOps modules
- Receive a professional certificate on course completion
- Interview question bank plus detailed interview preparation
- Curriculum designed by top MLOps professionals
- Real-time projects for hands-on MLOps skill building
- LinkedIn optimisation, resume building, mock interviews
- Trusted by 4,500+ learners for MLOps in Hyderabad
MLOps Training Course Curriculum in Hyderabad
MLOps Training Course Syllabus
1. Editing for movies, YouTube, and TV channels
2. Wedding and event video editing workflows
3. Marketing & corporate video presentation editing
4. Using AI tools alongside Premiere Pro
5. Integrating with Photoshop and After Effects for final outputs
6. New features overview
7. Non‑linear editing concepts
8. Standard digital video workflow
9. Integrating other components in the edit workflow
10. Adobe Production Premium workflow overview
11. Choosing project settings by sequence
12. Specifying and adjusting project & sequence settings
13. User preference configuration
14. Importing assets and images; image tips
15. Managing media in bins and finding assets
16. Building a rough cut with a storyboard
17. Automating storyboard to sequence
18. Editing clips on the Timeline & trimming
19. Ripple edit; moving clips within the Timeline
20. Adding clips via Source Monitor & its tools
21. Time‑saving edit tools overview
22. Rolling, slide, and slip edits
23. Lift and Extract operations
24. Replace Clip and Replace Footage features
25. Sync Lock & Track Lock; finding timeline gaps
26. Best practices for transitions
27. Changing parameters in Effect Controls panel
28. A/B mode fine‑tuning
29. Managing head/tail handle limitations
30. Applying transitions to multiple clips; adding audio transitions
31. Slow‑motion and reverse‑motion techniques
32. Rate Stretch tool
33. Time remapping with speed transitions and reverse
34. Downstream effects of time changes
35. Batch changing speed for clips and stills
36. Voice recording setup and narration techniques
37. Audio characteristics and levels
38. Adjusting volume in Effect Controls; gain
39. J‑cuts and L‑cuts for smoother edits
40. Audio effects and clip keyframing
41. Working with the Audio Mixer; automation
42. Submixes and voice‑over recording
43. Creating a 5.1 surround mix
44. Cleaning noisy audio; Adobe Soundbooth workflow
45. Title design fundamentals
46. Text parameters and building text
47. Text on a path and shape creation
48. Aligning shapes; rolls and crawls
49. Sheens, strokes, shadows and fills
50. Compositing concepts and planning shots
51. Opacity and blend modes
52. Alpha channels and graphic file alphas
53. Green‑screen keying with Ultra Key
54. Matte keys, Track Matte Key, and traveling mattes
- 55. Speech‑to‑text transcription
56. Improving speech analysis accuracy
57. Keyword searching in transcriptions
58. Setting In/Out using analysis text
59. Metadata modification; face detection
60. Overview of color‑oriented effects
61. Removal/replacement and technical color effects
62. Fast Color Corrector, Auto Color, Leave Color
63. Change to Color, Color Balance (RGB)
64. Using nested sequences in color workflows
65. P2, XDCAM, AVCHD and DSLR formats
66. Media Browser for import
67. Importing P2 and understanding folder structure
68. Importing AVCHD and mixing media formats
69. Multiple uses for nested sequences
70. Nesting clips for complex edits
71. Export options overview
72. Exporting single frames and via Export Settings
73. Adobe Media Encoder formats & usage
74. Export to mobile and Final Cut Pro
75. Working with EDLs; tape/analog recording options
76. Project menu overview
77. Making a clip offline
78. Project Manager and trimmed projects
79. Collecting files and copying to a new location
80. Final project management; importing projects/sequences
Explore motion graphics and VFX to bring your videos to life with animations and visual effects. You’ll learn intros, title animations, green-screen work, and professional compositions.
81. Working with ready‑made After Effects templates
82. Creating custom templates for reuse
83. Title animations, logo animations for TV/YouTube/films
84. 3D animation basics and workflows
85. Green/blue screen keying; color grading in AE
86. Using AI tools within After Effects
87. Analog vs. digital video
88. Frame rate and resolution
89. Storage space planning
90. System requirements
91. Defining motion graphics
92. Creating a project and panel layout
93. Project, Composition, and Timeline windows
94. RAM Preview vs. Standard preview
95. Importing media files, PSD and AI
96. Previewing footage, stills and audio
97. Trimming clips; interpret footage
98. Looping audio/video
99. Layer types and options
100. Creating solids; layer switches
101. Time stretch and frame blending
102. Nesting compositions and using precomps
103. Animating layer properties
104. Parenting for reusable motion
105. Motion paths and layer blending
106. Controlling speed; easing principles
107. Creating and formatting text
108. Character and Paragraph palettes
109. Text animation with keyframes and presets
110. Using Adobe Bridge with AE
111. Mask creation and animation
112. Alpha channels and track mattes
113. Effect application fundamentals
114. Animating effects over time
- Capabilities and limitations
116. 3D layers and multi‑viewports
117. 3D transforms and animation
118. Creating and using lights
119. Render queue and formats
120. Render settings and templates
121. Duplicating jobs; exporting project files
122. Rendering individual frames
Master image editing, retouching, and visual design skills that every video editor needs. You’ll work on thumbnails, posters, and creative assets for videos and social media.
123. Generative Fill and AI‑powered retouching
124. Logo and album design workflows
125. Background removal and color correction with AI
126. Green/blue screen removal techniques
127. YouTube/Instagram/Facebook thumbnail creation
128. Flyer and business card design; print sizes & formats
129. Telugu typing without Anu Script
130. Creating composites, graphics and digital art
131. Menus, options bar, tools panel and panels
132. PC vs. Mac differences
133. Zoom methods and hidden tools
134. Why selections matter
135. Geometric, freehand and edge‑based selections
136. Color‑based selections
137. Choosing the right selection tool
138. Color/tonal adjustments and adjustment layers
139. Presets and common corrections
140. Saving/deleting adjustments; applying to layers
141. Blur, Sharpen and Smudge
142. Dodge, Burn and Sponge tools
143. Image modes, resolution and size
144. Straighten, crop and rotate
145. Auto color; manual color cast removal
146. Tonal range adjustments and Replace Color
147. Clone, Spot Healing, Healing Brush, Patch and Content‑Aware Fill
148. Background vs regular layers
149. Hide/view/reposition/delete/rename/merge
150. Locking and converting background layer
151. Layer styles and applying to multiple layers
152. Gradient tool and styles
153. Editing/saving gradients
154. Masks vs selections; Quick Mask
155. Brush & Channels panel; load mask as selection
156. RAW concepts and advantages
157. White balance, tonal range, saturation and sharpening
158. Camera formats (NEF/CRW/ORF), DNG workflow
159. Bridge vs Photoshop; synchronize corrections
160. Shadows/Highlights adjustments
161. Red eye correction and edge sharpening
162. Lens distortion correction and depth of field effects
163. Point vs Paragraph type; character & paragraph panels
164. Type on a path; warp; work paths
165. Convert type to shapes; type masks and selections
166. Clipping mask with type; OpenType features
167. Bitmap vs vector basics
168. Pen tools (standard, magnetic, freeform)
169. Converting selections to paths/layers
170. Shape layers and Smart Objects
171. Animating GIFs for the web
- Channels & masking; color basics
173. Advanced layered techniques - Editing prominent colors in a scene
175. Generating background ideas for composites
Learn how to create stunning graphics, layouts, and designs that support your video projects. This module helps you design posters, titles, and creative elements to use in editing.
176. Getting started and screen layout
177. File management and page setup
178. Navigation, viewing modes and multi‑page documents
179. Inserting/deleting pages; page changes
180. Multiple workspaces and toolbar customization
181. Shortcuts and default settings
182. File backup options
183. Drawing and shaping tools
184. Freehand lines, polylines and polygons
185. Perfect shapes, rectangles and circles
186. Reshaping lines and curves
187. Select/deselect, move, copy and delete
188. Sizing, mirroring, rotating and skewing
189. Using the Transform docker
190. Eyedropper and Paint Bucket
191. Outline tool: thickness and colors
192. Fill tool: uniform, fountain, pattern
193. Interactive mesh fill and copying attributes
194. Setting outline/fill defaults
195. Arrange, group/ungroup and alignment
196. Guidelines, dynamic guides and Snap To
197. Group/child objects; combine/break; weld/intersect/trim
198. Layer creation, master layers and Object Manager
199. Move/copy/lock and reorder layers
200. Artistic Media and Envelopes
201. Extrude and Blend
202. Lens effects and Perspectives
203. PowerClip, Contours and Drop Shadows
204. Interactive fills, Distortions, Transparencies and Mesh
205. Artistic vs Paragraph text
206. Editing and formatting text; options
207. Indents, importing text and spell‑check
208. Color management and custom palettes
209. Color harmonies and styles; Color Docker
210. Paragraph frames, text flow and formatting
211. Wrap around objects, Drop Caps and typing into shapes
212. Fit text to path; convert to curves
213. Blended text shadows and special styles
214. Jumpy, Neon, Glow, Chrome, Bevel text
215. Enveloped text effects
216. Inserting text symbols and clipart; modifications
217. Bitmap concepts and import options
218. Color adjustments and bitmap effects
219. Creating web images and advanced GIF options
220. Greeting cards and special page layouts
221. Labels and print preview
222. Exporting to graphic formats; copy/paste to apps
223. Creating/applying styles; copying properties
224. Custom patterns; managing symbols
225. Graphic formats overview
226. Corel Trace basics and image tracing
227. Importing traced files into CorelDraw
MLOps Training Roadmap – Beginner to Advanced
MLOPS class Roadmap
Our MLOps training in Hyderabad follows a structured 3-month pathway divided into three key phases. Each phase equips you with vital MLOps concepts, hands-on cloud integration skills, and real industry projects for AI/ML operations career growth. This program also includes flexible MLOps online training options to suit your learning style and schedule.
01
Month 1: Python for ML, Foundations of MLOps & Version Control
- Start with core Python for ML and scripting, Linux/Bash essentials, and fundamentals of machine learning operations.
- Learn version control using Git and GitHub for ML collaboration and code management.
- Explore workflow orchestration concepts, basic CI/CD, and an introduction to Docker for containerization.
- Work on foundational projects, including setting up code repositories, simple model training scripts, and basic automation.
02
Month 2: Model Deployment, Cloud MLOps & Experiment Tracking
- Advance to deploying ML models using Flask, FastAPI, and REST APIs.
- Gain practical skills in Docker and Kubernetes for automated model scaling and container orchestration.
- Work with leading MLOps tools: MLflow, Kubeflow, and integrate pipelines with cloud platforms (AWS Sagemaker, Azure ML, Google Vertex AI).
- Build projects focused on automating the ML lifecycle—training jobs, experiment tracking, and pipeline execution.
03
Month 3: Monitoring, Automation, Capstone Projects & Career Prep
- Master model monitoring and drift detection tools, automated retraining strategies, and production-level ML governance.
- Implement advanced CI/CD (Jenkins, GitHub Actions), logging, and alerting with Prometheus and Grafana.
- Work on a capstone project: build end-to-end ML pipelines, deploy in the cloud, and integrate monitoring and alerts.
- Prepare for placement with interview Q&A, resume building, mock interviews, and LinkedIn/profile optimisation.
What is MLOPS?
- MLOps applies DevOps principles to machine learning workflows and models.
- It streamlines the machine learning lifecycle from development through deployment, monitoring, and maintenance.
- MLOps bridges data scientists, ML engineers, and IT operations for seamless model delivery.
- It automates tasks such as data preparation, model training, deployment, and monitoring.
- Covers data validation, feature engineering, model versioning, deployment, and continuous monitoring.
- Ensures model reproducibility, traceability, and continuous integration/continuous deployment (CI/CD) for ML.
- Improves model monitoring, automated retraining, and governance.
- Helps scale ML in production, handle model drift, and accelerate business impact.
- Enables collaboration across teams to maintain high model performance over time.
- Provides a structured, automated, and collaborative approach to managing ML in production environments.
Where are MLOps used?
Industry Sector | Data Analytics Application | Real-World Example |
Retail & E-commerce | Personalised recommendations, dynamic pricing | Amazon uses MLOps for personalised product suggestions and dynamic pricing strategies. |
Healthcare | Medical imaging analysis, patient diagnostics | Hospitals use AI models for early cancer detection with secure, compliant MLOps pipelines. |
Manufacturing | Predictive maintenance and operational efficiency | General Electric uses MLOps for monitoring turbines and predicting equipment failures. |
Financial Services | Fraud detection, credit scoring, and loan approval | JPMorgan Chase automates fraud detection model updates with MLOps practices. |
Agriculture | Crop monitoring and yield prediction | AgroScout leverages MLOps to automate crop production analytics and accelerate experiments. |
Telecom | Customer churn prediction and retention | Vodafone uses MLOps to update churn prediction models for targeted customer retention. |
Supply Chain & Logistics | Demand forecasting, inventory optimisation | Walmart employs MLOps to optimise the supply chain and maintain inventory levels efficiently. |
Pharmaceuticals | Drug discovery and clinical trial optimisation | Pfizer uses MLOps to accelerate drug discovery by automating model retraining and testing. |
Benefits of the MLOps Course in Hyderabad
Benefits of the Course
1. Learn from MLOps Experts
Gain step-by-step practical training using real industry MLOps workflows, taught by professional ML engineers and DevOps specialists.
2. Master MLOps Tools
Hands-on with Git, Docker, Kubernetes, MLflow, Kubeflow, and cloud ML platforms for real-world automation.
3. Hands-On Real World Projects
Build portfolio-ready projects covering ML model deployment, pipeline automation, performance monitoring, and production-grade workflows.
4. Career & Placement Support
Resume building, job referrals, interview prep, and ongoing mentorship focused on MLOps and AI/ML roles.
5. Earn a Globally-Recognised Certification
Receive an MLOps certificate demonstrating skills in CI/CD, automated model management, and ML system reliability.
6.Develop a Strong Python & Cloud Foundation
Master Python for ML automation, plus cloud platform fundamentals (AWS, Azure, GCP) for scalable deployments.
7. Understand ML Pipelines & Model Management
Learn data workflow orchestration, pipeline scheduling, versioning, and model registry management.
8. Text Analytics & Model Monitoring
Implement sentiment analysis, track model drift, and set up alerting and monitoring dashboards.
9. Create Dashboards & Visualise Operations
Use advanced visualisation tools to monitor ML operations, pipeline status, and data quality.
10. Big Data & ETL Expertise
Integrate large-scale data ingestion, preprocessing, and ETL with MLops best practices.
11. Industry-Relevant MLOps Skills
Develop expertise for applying MLOps in finance, healthcare, telecom, retail, and product companies.
12. Statistical & Analytical Confidence
Build confidence in statistics, model evaluation metrics, and continuous model refinement.
13. Flexible Learning: Classroom & Online
Enjoy multiple learning modes: live, hybrid, weekend, and online classes for all backgrounds.
14.Affordable Fees & EMI Options
Take advantage of competitive pricing and simple EMI plans for career-ready MLOps training.
15. Peer & Alumni Community Access
Connect with mentors, batchmates, and working MLOps engineers for lifelong learning and support.
16. Upgrade with Latest MLOps Tools
Stay updated on new releases of MLops frameworks, cloud DevOps tools, and open-source innovations.
17. Work on Capstone Production Projects
Lead and document a full-scale MLOps project: from data preprocessing to deployment and monitoring.
18. Continuous Access & Support
Get unlimited access to all course material, along with rapid-response faculty and tech support.
Thinking of MLOps Training in Hyderabad?
- Traditional Training
- You listen passively, minimal engagement
- Focuses on outdated slides, less practical
- Trainers with only basic knowledge
- Rare hands-on, limited exposure
- Support ends after the course
- Small exercises, little business context
- No/low placement or interview prep
- Generic, pre-recorded content
- One-size-fits-all curriculum
- No dedicated MLOps training track
- Brolly Academy MLOps Training
- You code and solve real MLOps projects from day one
- Learn the latest MLOps tools: Python, Docker, Git, MLflow, Kubeflow, cloud platforms
- Mentoring by industry experts in MLOps, AI, and cloud engineering
- Daily labs on model deployment, pipelines, monitoring, and automation
- Ongoing job placement & portfolio guidance until you get hired
- Resume building, interview practice, LinkedIn optimization
- Custom mentorship and live peer discussions (WhatsApp, Discord)
- Tailored modules covering ML lifecycle, automation, cloud, and security
- Specialised MLOps career tracks with mentorship for ML engineers and data scientists
Best MLOPS Training Institute in Hyderabad
Meet Our MLOPS Trainer
INSTRUCTOR
Dr. Raju
MLOps Instructor & Cloud ML Specialist
13+ Years in Machine Learning Operations, DevOps, and Cloud Engineering
About the tutor:
- Has trained over 350 students in Hyderabad
- Expert in Python, Docker, Kubernetes, Git, CI/CD, MLflow, Kubeflow, and cloud ML platforms (AWS, Azure, GCP)
- Projects: Model deployment for healthcare analytics, automated retraining for financial forecasting, ML pipeline monitoring in retail and supply chain companies
- Teaching Style: Interactive and practical, focused on live coding, hands-on production projects, and mentoring freshers and working pros into job-ready MLOps engineers
Skills You’ll Gain from MLOps Classes in Hyderabad
Skills Developed after the course
- Build and deploy complete MLOps projects using Python, Git, Docker, Kubernetes, and MLflow in real-world production environments.
- Design, manage, and optimise scalable CI/CD pipelines to automate ML model training, testing, and deployment.
- Master data preparation, transformation, and automated data validation using orchestration tools and pipelines.
- Develop and interpret monitoring dashboards for model drift, health, and performance in production systems.
- Apply statistical analysis, model evaluation metrics, and version control to track and improve model accuracy.
- Implement machine learning model deployment using cloud platforms like AWS SageMaker, Azure ML, and Google Vertex AI.
- Automate experiment tracking, model registry, and versioning with industry-standard tools for reproducible results.
- Analyse and troubleshoot ML models using advanced monitoring, logging, and alerting frameworks.
- Manage end-to-end ML lifecycle, including automated retraining, continuous deployment, and pipeline security.
- Apply project-based learning: automate real-time ML systems, handle dynamic data, and work on cloud-based projects for domains like finance, healthcare, and retail.
- Use Grafana, Prometheus, and visualisation tools to monitor, alert, and optimise production ML pipelines.
- Practice interview questions, resume building, LinkedIn portfolio enhancement, and peer networking for MLOps roles.
- Gain industry exposure with MLOps certifications, mock interviews, and networking opportunities for job placement.
- Build an MLOps portfolio of capstone projects reflecting real business impact using Hyderabad’s tech market needs.
- Understand cloud service integration, ML lifecycle management, MLOps security, and DevOps alignment.
- Develop strong mathematical, statistical, and programming foundations essential for MLOps and AI/ML engineer career growth.
MLOPS Course Institute in Hyderabad
MLOPS Capstone Projects Covered
At Brolly Academy, our MLOps course lets you work on real projects so you can learn how machine learning models are used in businesses. Whether you take the class in person or online in Hyderabad, these projects help you get ready for jobs in IT, finance, healthcare, and more. You will build experience by doing hands-on work that will make you confident and ready to start a career.
1.End-to-End ML Model Deployment
Build, containerise, and deploy machine learning models using Python, Docker, and Kubernetes with automated CI/CD pipelines for retail inventory prediction.
2. Customer Segmentation ML Pipeline
Implement clustering algorithms in scalable ML pipelines using Kubeflow and MLflow, enabling marketing teams to automate segment-specific model deployment.
3. Financial Risk Model Monitoring Dashboard
Create real-time dashboards with Prometheus and Grafana, monitoring model drift and performance for risk assessment in finance and banking.
4. Big Data ML Pipeline with Spark & Airflow
Build automated data ingestion and preprocessing workflows for large-scale retail datasets, integrating Apache Spark and Airflow for anomaly detection.
5. Enterprise Model Registry & Governance
Establish a centralised model registry and governance workflows using MLflow and cloud services, tracking multiple versions and supporting executive ML reporting.
6. Personalised Recommendation API Deployment
Develop and deploy a real-time recommendation API (for e-commerce or OTT platforms) in hybrid cloud environments, integrating collaborative filtering with continuous model retraining.
Tools Covered in MLOps Training in Hyderabad
Tools Covered
MLOPS course in Hyderabad fees
MLOps Course Fee & Offerings in Hyderabad
Video Recording
Rs 15000 9999
- Lifetime access to MLOps video modules and recorded classes
- Covers: Python for ML, Docker, Kubernetes, CI/CD, cloud deployment, and monitoring
- 80+ recorded lessons
- 1 MLOps capstone deployment project included
- Resume & interview support
- 100% placement assistance
- WhatsApp group for Q&A
Class Room Training
Rs 35000 29999
- 2–3 months structured classroom MLOps training
- Expert trainers with real MLOps & cloud experience
- Real-industry projects: ML pipeline automation, cloud model deployment, monitoring dashboards
- One-on-one mentorship & lab assistance
- Monthly mock interviews
- Resume building & interview practice
- Soft skills & aptitude training
- Dedicated placement officer
- Offline batch commute support
- WhatsApp support & peer group
Online Course
Rs 30000 24999
- Live interactive online classes (timings to suit working pros or students)
- 2–3 months duration, daily session recordings
- Project environment from Day 1 until placement
- Weekly mock interviews
- 50+ sample project resources
- Doubt-clearing sessions
- WhatsApp group support
Placement Program for MLOps Training in Hyderabad
Placement Program
At Brolly Academy, the MLOps course in Hyderabad includes a 100% placement support program to ensure you not only master industry-relevant MLOps skills but also launch your career with top companies.
Resume Building
Placement Training
Interview Questions
Realtime Live Projects
Get Offer Letter
Scheduling Interviews
Mock Interviews
Personality Development
- Resume Building: Create ATS-friendly resumes tailored for MLOps, ML engineering, and DevOps roles.
- Placement Training: Learn how to apply for jobs, target openings, and succeed in company-specific hiring processes.
- Interview Questions Prep: Get access to MLOps and technical interview question banks (deployments, CI/CD, monitoring).
- Internships Under Experts: Gain hands-on internship opportunities to work on real MLOps and cloud deployment projects.
- Real-Time Projects: Build a practical portfolio with MLOps pipeline automation, cloud model deployment, and monitoring use cases.
- Aptitude Preparation: Improve logical reasoning, coding, and technical problem-solving for MLOps interviews.
- Personality Development: Build communication, confidence, and presentation skills for client and team interactions.
- Mock Interviews: Practice with industry professionals and HR, focusing on real-world MLOps interview scenarios.
- Scheduling Interviews: Connect with hiring partners and receive personalised interview scheduling support.
- Get Offer Letter: Secure job offers from leading companies in Hyderabad and across India.
MLOPs training institute in India
Testimonials
MLOPS Student Community in Hyderabad
Student Community
At Brolly Academy, joining the MLOps course means becoming part of a collaborative, active student community. Connect, learn, and grow alongside fellow MLOps learners and industry experts in India.
Learning & Collaboration
Work with peers on real MLOps projects. Share Python, Docker, and cloud deployment tips. Solve production ML challenges together as a team.
Access to Resources and Tools
Get exclusive access to MLOps tools (Git, Docker, Kubernetes, MLflow, Kubeflow, AWS, Azure, GCP), datasets, and recorded expert sessions for ongoing learning.
Networking Opportunities
Expand your professional network by connecting with MLOps trainers, mentors, and tech recruiters in Hyderabad and across India.
Mentorship from Industries Professional
Receive expert guidance and project feedback from senior MLOps engineers and cloud specialists. Gain career advice and real-world project insights.
Job Support and Career Development
Stay updated with the latest MLOps job opportunities, internships, project work, and receive dedicated placement assistance.
MLOPS Training in Hyderabad
Pre-requisites & Eligibility
- No Technical Skills Required – You don’t need advanced programming or data science expertise to join our MLOps training institute in Hyderabad. Basic knowledge of computers and cloud concepts is enough to get started.
- Students & Graduates – Whether you’re currently pursuing your degree or have just completed it, this MLOps certification course in Hyderabad is open to students from all technical and non-technical backgrounds who want to enter the AI and ML industry.
- Working Professionals – IT professionals, data engineers, DevOps engineers, or software developers can upskill to automation and deployment in machine learning with our advanced MLOps course in Hyderabad.
- Entrepreneurs & Startups – Learn how to integrate machine learning models into production, automate workflows, and optimise your AI-driven business operations using tools like Docker, Kubernetes, and CI/CD pipelines.
- Freelancers – Build expertise in ML model deployment, cloud-based MLOps tools, and monitoring solutions to offer MLOps services independently.
- Job Seekers – Perfect for freshers who want placement-focused MLOps training in Hyderabad with hands-on experience in real-world projects and end-to-end ML lifecycle management.
- Eligibility Age – Open to learners aged 18 years and above who are passionate about AI, machine learning, and automation technologies.
- Global Career Aspirants – Since MLOps is one of the fastest-growing global career fields, our MLOps training in Hyderabad equips you for in-demand roles in India and remote positions worldwide.
Who Should Learn the MLOps course in Hyderabad?
- Data Scientists: Those looking to deploy, manage, and monitor models in real production environments.
- ML Engineers: Anyone wanting to build robust ML pipelines and automate workflow from model training to deployment.
- DevOps & Cloud Engineers: IT professionals interested in expanding into ML-focused CI/CD and automation with cloud integration.
- Software Developers: Developers aiming to transition into AI/ML roles or add scalable ML deployment skills.
- Project Managers & Tech Leads: Leaders who manage AI and ML application delivery and want to understand the MLOps process.
Career Opportunities After MLOps Training in Hyderabad
Career Opportunities
- MLOPS Engineer: Manage and automate ML model deployment and monitoring pipelines.
- Machine Learning Engineer: Develop and optimise machine learning models for production.
- Data Engineer: Build data pipelines and infrastructure for ML workflows.
- DevOps Engineer: Implement CI/CD and cloud automation for ML and application deployments.
- ML Operations Manager: Oversee MLOps teams and end-to-end model lifecycle management.
- Cloud Engineer: Design and manage cloud environments for scalable ML applications.
- Data Scientist with MLOps Expertise: Analyse data and implement production-ready ML models.
- AI/ML Solutions Architect: Architect AI and ML solutions incorporating MLOps best practices.
- Machine Learning Platform Engineer: Develop and maintain platforms supporting ML automation and scaling.
Over 20,000+ job openings available for MLOPS in Hyderabad for freshers
MLOps Salary in Hyderabad by Experience Level
Experience Level | Average Salary (INR per annum) | Description |
Entry-Level (0-2 years) | ₹6 – ₹10 LPA | Beginners learning deployment, monitoring, and basic infrastructure. |
Mid-Level (2-5 years) | ₹12 – ₹18 LPA | Managing ML pipeline automation and mentoring juniors. |
Senior-Level (5+ years) | ₹20 – ₹28 LPA | Leading ML ops teams, strategic planning, and optimisation. |
MLOPS Salaries In India
Hiring Companies for MLOPS Professionals from Brolly Academy
Best MLOPS training institute in Hyderabad with placement
Our Achievements
Completed 150+ Batches
12+ Years Leading MLOps & Machine Learning Operations training
4,500+ Students Across MLOps, AI, and Data Engineering programs
20+ Capstone Projects Real-time MLOps projects on MLflow, Kubeflow, Azure ML, AWS Sagemaker
MLOps Certification in Hyderabad
These certifications validate your expertise in MLOps pipelines, cloud deployment, and real-world ML automation, giving you an edge in Hyderabad’s competitive tech job market
MLOps Certifications will guide On
At Brolly Academy, you receive industry-recognised MLOps certifications upon successful completion of your training. This certification demonstrates your hands-on expertise in automating ML pipelines, deploying models with Docker and Kubernetes, and using top MLOps tools in production. Having this credential boosts your resume and helps you qualify for roles in AI/ML engineering, cloud deployment, and DevOps.
- Brolly Academy MLOps Certification (on course completion)
- Microsoft Certified: Azure DevOps Engineer Expert
- AWS Certified Machine Learning – Speciality
- Google Professional Machine Learning Engineer
- Google Cloud Professional DevOps Engineer
- IBM AI Engineering Professional Certificate
- Databricks Certified Machine Learning Professional
- Coursera MLOps Specialisation (Stanford / DeepLearning.AI)
- TensorFlow Developer Certificate
- Cloudera Data Platform Generalist Certification
Market Trends for MLOps training in Hyderabad
Market Trends
- Rapid Market Growth: The global MLOps market was valued at over USD 2.1 billion in 2024 and is expected to grow at a CAGR of around 40% reaching USD 16.6 billion by 2030. This growth is fueled by increasing AI and ML adoption across industries seeking scalable, automated model deployment and management.
- AI Automation & AutoML: Automation is transforming model training, deployment, and monitoring. Tools enabling auto-retraining triggered by data changes help enterprises maintain model accuracy without manual effort.
- Cloud & Platform Expansion: Cloud-based MLOps platforms like AWS, Azure, and Google Cloud provide scalable infrastructure critical for handling large datasets and ML workflows. On-premises deployments remain significant but cloud adoption is rising fast.
- Integration with DevOps: MLOps practices increasingly integrate with DevOps, creating unified pipelines for both software and ML models, improving collaboration, and speeding releases.
- Model Governance & Ethical AI: Focus on transparency, explainability, and compliance drives investments in tools to monitor bias, drift, and model behaviour within regulated industries.
- Industry Applications: BFSI leads in applying MLOps for fraud detection and credit risk. Healthcare and retail follow with personalised recommendations, predictive maintenance, and diagnostics.
- Talent Demand: Specialized MLOps engineering roles are booming as organizations need experts to operationalize AI solutions at scale with reliability.
Frequently Asked Questions – MLOps Training at Brolly Academy, Hyderabad
FAQS
1. What is MLOps and why is it important?
MLOps combines machine learning and DevOps practices to automate and manage the ML lifecycle, ensuring reliable model deployment and monitoring.
2. What is taught in MLOps training in Hyderabad?
Training covers Python for ML, CI/CD pipelines, containerization (Docker/Kubernetes), cloud deployment (AWS/Azure/GCP), monitoring, and automation tools like MLflow and Kubeflow.
3. How long does it take to learn MLOps?
Typically 2–3 months of structured learning, including hands-on projects.
4. Is MLOps training good for freshers?
Yes, beginners with Python basics can start and build practical skills step-by-step.
5.What is the salary of an MLOps engineer in Hyderabad?
Salaries range from ₹6 LPA for freshers to ₹28 LPA for experienced professionals.
6. Which is the best institute for MLOps training in Hyderabad?
- Brolly Academy is a leading institute offering comprehensive, hands-on MLOps training with placement support.
7. What skills are required for MLOps?
Python programming, ML basics, DevOps concepts, containerization, CI/CD, cloud platforms, and monitoring tools.
8. How do I start a career in MLOps?
Learn foundational Python and ML, then enrol in an MLOps course with real projects and certification.
9. Is MLOps in demand in India?
Yes, demand is rising as companies deploy AI and ML models in production.
10. What are the prerequisites for MLOps training?
Basic Python knowledge, understanding of ML concepts, and familiarity with Git are recommended.
11. Does MLOps require coding knowledge?
Yes, Python and scripting skills are essential.
12. What is the difference between DevOps and MLOps?
DevOps focuses on software delivery pipelines; MLOps extends this to ML model lifecycle, including training, deployment, and monitoring.
13. Which companies in Hyderabad hire MLOps engineers?
Leading IT firms, AI startups, fintech companies, and cloud service providers.
14. What tools are used in MLOps projects?
MLflow, Kubeflow, Docker, Kubernetes, Jenkins, Airflow, Prometheus, Grafana, cloud ML platforms.
15. How does MLOps work with cloud platforms like AWS and Azure?
Cloud platforms provide scalable infrastructure and services to deploy and monitor ML models seamlessly.
16. Can I learn MLOps online?
Yes, Brolly Academy offers interactive online MLOps courses.
17. Is MLOps difficult to learn?
It requires effort, but structured training and hands-on projects make it manageable.
18. What is the cost of the MLOps course in Hyderabad?
Starts around ₹15,000 for video courses to ₹45,000 for classroom training.
19. Do MLOps institutes in Hyderabad offer placement assistance?
Yes, Brolly Academy provides dedicated placement support and interview coaching.
20. What is an MLOps pipeline?
A series of automated steps for data processing, model training, testing, deployment, and monitoring.
21. What are the real-time applications of MLOps?
Fraud detection, predictive maintenance, recommendation systems, healthcare diagnostics, and more.
22. What programming languages are needed for MLOps?
Mainly Python; some knowledge of shell scripting and YAML is helpful.
23. Can I transition from data science to MLOps?
Yes, by learning automation, deployment, and DevOps tools.
24. How do MLOps tools like MLflow and Kubeflow work?
They help track experiments, manage model versions, and automate deployment pipelines.
25. Which cloud is best for learning MLOps?
- AWS, Azure, and Google Cloud are all widely used; learning any of these is beneficial.
26. What are the industry-recognised MLOps certifications?
Certifications from cloud providers and specialised MLOps programs add value.
27. What are the benefits of learning MLOps in 2025?
- Increased job demand, better project scalability, and faster AI innovation cycles.
28. How is MLOps related to AI and Data Science?
MLOps operationalises AI models developed by data scientists, enabling reliable production use.
29. Is there any MLOps certification available in Hyderabad?
Yes, Brolly Academy offers recognised certification after course completion.
30. What job roles can I get after completing MLOps training?
MLOps Engineer, ML Engineer, DevOps Engineer, Data Engineer, Cloud Engineer, and more.
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