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MLflow

Track Experiments, Manage Models, and Deploy ML Workflows with MLflow

In this course, you will: Set up MLflow tracking server with PostgreSQL backend and S3 artifact store; Log parameters, metrics, tags, and artifacts in training experiments; Compare runs, visualize metrics, and select best models from the MLflow UI.

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MLflow

43+

Hours

13

Modules

14

Topics

4.7

Rating

Beginner-Friendly

Level

New

Batches weekly

About MLflow

Track Experiments, Manage Models, and Deploy ML Workflows with MLflow

In this course, you will: Set up MLflow tracking server with PostgreSQL backend and S3 artifact store; Log parameters, metrics, tags, and artifacts in training experiments; Compare runs, visualize metrics, and select best models from the MLflow UI.

What This Training Covers

The MLflow programme at Tutorsbot spans 43+ hours across 13 structured modules. Every module is built around hands-on projects and real-world scenarios — not slide-heavy theory. Your instructor walks you through each concept with live demonstrations, code reviews, and practical exercises so you can apply what you learn from day one. The curriculum is aligned with current Technology Training industry expectations and hiring patterns.

Enrollment & Training Quality

MLflow is available in 2 flexible learning modes — choose online live classes, classroom, hybrid, self-paced, or one-on-one depending on your schedule. Every batch is limited in size to ensure each learner receives personal attention, code-level feedback, and doubt resolution. Career support and certification are included with every enrolment. Tutorsbot instructors are working professionals who teach from delivery experience, and the training standard stays consistent across all modes and batches.

Course Curriculum

13 modules · 14 topics · 43 hrs

01

MLflow Architecture and Setup

7 topics

  • MLflow components — Tracking, Projects, Models, Registry, and Recipes
  • MLflow tracking server — Localhost, remote, and managed Databricks deployment
  • Backend store — SQLite, PostgreSQL, and MySQL for run metadata storage
  • Artifact store — Local, S3, Azure Blob, and GCS for artifact storage
  • MLflow UI overview — Experiments, runs, models, and comparison dashboards
  • Authentication and multi-user setup for team MLflow deployments
  • MLflow Python SDK — mlflow module, client API, and tracking context
02

Experiment Tracking

7 topics

  • Starting tracking runs with mlflow.start_run and context manager
  • Logging parameters — mlflow.log_param and mlflow.log_params
  • Logging metrics — mlflow.log_metric, mlflow.log_metrics, and step-based logging
  • Logging artifacts — Files, images, plots, and model checkpoints
  • Run tags and descriptions for search and organization
  • Nested runs — Parent-child run hierarchy for hyperparameter sweeps
  • Auto-logging — mlflow.autolog for scikit-learn, XGBoost, PyTorch, and Keras
03

Run Comparison and Visualization

Topics included

10 more modules available

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Enrol in This Course

All prices inclusive of 18% GST. Same curriculum & certification across all formats. Updated Aug 2026.

✓ 7-day refund guarantee✓ Same certificate for all formats✓ Lifetime access to recordings

Online Live

Live instructor-led sessions from anywhere, with recordings for catch-up.

₹14,999incl. GST

GST ₹2,288 included

EMI from ₹2,500/mo

or

What You Get After Completion

Every graduate receives a verified certificate, a portfolio of real projects, and dedicated career support.

Verified Certificate

Digitally signed with a permanent shareable link — not just for attendance.

LinkedIn-importable·Permanent URL·PDF download

Project Portfolio

Real, deployable projects reviewed by your instructor — ready for interviews.

Instructor-reviewed·GitHub-hosted·Interview-ready

Career Support

Résumé review, mock interviews, LinkedIn guidance, and employer introductions.

1-on-1 coaching·Mock interviews·Employer connect

Meet Your Instructor

Every MLflow batch is led by a practitioner who teaches from production experience, not textbooks.

Industry Expert

Tutorsbot Assigned

Senior Technology Professional

10+ yrs experience

Senior professionals with substantial hands-on delivery experience at top companies, bringing real-world projects, industry insights, and best practices.

How We Teach

  • Concepts start with a real problem so theory lands in context
  • Projects reviewed the way a senior colleague reviews pull requests
  • Every topic includes the kind of questions you'll face in interviews
Hire Trained Talent

Hire MLflow Talent from Tutorsbot

Companies hiring MLflow talent from Tutorsbot receive pre-assessed profiles backed by project work, instructor review, and interview-ready candidates who can explain what they built and why.

Why hire from us

Project repositories with documented technical decisions

Assessment outcomes backed by instructor context

Candidate readiness shaped by interview-style practice

Project-based portfolios available

Frequently Asked Questions

Everything you need to know about MLflow, answered by our training experts

1Who should take MLflow?
This programme is ideal for Data scientists who want systematic experiment tracking instead of manual notes, ML engineers building reproducible training pipelines for team collaboration, MLOps engineers setting up a centralized model registry and lifecycle system. Whether you are a fresh graduate looking for your first role, a working professional aiming for a promotion, or a career switcher exploring a new domain, this course meets you where you are with personalised learning paths.
2Does MLflow include a certificate?
Absolutely. Upon successful completion of MLflow, you will receive an industry-recognised certificate from Tutorsbot that you can share on LinkedIn, attach to your résumé, and present at job interviews. Our certificates are built to support hiring conversations across India and international teams.
3Is placement support included with MLflow?
Yes. Every MLflow enrolment includes our comprehensive placement support programme. This covers one-on-one résumé building, LinkedIn profile optimisation, mock interview sessions with industry experts, soft-skills workshops, and direct job referrals through our hiring network.
4How long does MLflow take to complete?
The full course spans 43+ hours of instructor-led training, typically delivered over 6–10 weeks depending on the batch schedule you choose. Self-paced learners can progress faster, while weekend batches allow working professionals to learn without disrupting their current role.
5What is the mode of delivery for MLflow?
MLflow is available in multiple modes: Online Live (real-time classes with an instructor), Classroom (in-person at our training centres), Hybrid (mix of online and classroom), and Self-Paced (pre-recorded with mentor support). Every mode includes the same curriculum, certificate, and placement support. Choose what fits your schedule best.
6Can I get a free demo class for MLflow?
Yes, Tutorsbot offers a complimentary demo session for every course. During the demo, you will meet your instructor, experience the teaching methodology, and get a detailed walkthrough of the course curriculum. This is a zero-obligation session. Join, evaluate, and then decide if the programme is right for you.
7What kind of projects will I work on in MLflow?
Throughout MLflow, you will work on 13+ real-world projects and case studies drawn from actual business scenarios. These projects are designed to build your portfolio and give you hands-on experience that you can showcase during job interviews. Our instructors review every project submission and provide personalised feedback.
8What if I miss a class?
We understand that life happens. If you miss a session, you can access the recorded video of the class within 24 hours. You can also join the next available batch for that specific module at no extra cost. Our support team will help you stay on track regardless of any interruptions.
9Is MLflow worth it for experienced professionals?
Absolutely. Many of our learners are already working professionals who enrol to upskill, transition into specialised roles, or earn a recognised credential. The MLflow curriculum includes advanced modules and real-world case studies that challenge experienced learners while filling practical gaps.
10What is the refund policy for MLflow?
Tutorsbot offers a 7-day money-back guarantee on all courses. If you are not satisfied with the quality of training within the first 7 days, you can request a full refund, no questions asked. We are confident you will love the experience, but we want you to enrol risk-free.
11Do you offer corporate or group training?
Yes. Tutorsbot works with enterprises on custom corporate training programmes. For MLflow, we offer dedicated batches, customised curriculum, flexible scheduling, team progress dashboards, and volume-based commercial options. Contact our corporate team for a tailored proposal.
12How are the instructors selected at Tutorsbot?
Every Tutorsbot instructor goes through a rigorous selection process. We require substantial hands-on industry experience, proven teaching ability, and strong communication skills. Our instructors bring real-world engineering and delivery insights directly into the classroom.
13Will I get lifetime access to MLflow materials?
Yes. Once you enrol in MLflow, you get lifetime access to all course materials, including recorded sessions, slides, code notebooks, assignments, and project files. As the curriculum gets updated, you automatically receive access to the latest content at no additional cost.
14Can I switch between batch timings?
Yes, Tutorsbot offers flexible batch transfers. If your current batch timing no longer works for you, simply reach out to our support team and we will move you to another batch: weekday mornings, evenings, or weekend batches, at no extra charge.
15What support do I get after completing the course?
Post-completion, you retain access to our alumni community, placement support for up to 12 months, and all updated course materials. Our career coaches continue to assist you with interview preparation, salary negotiation, and career guidance long after you finish the programme.

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