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IITM Pravartak Certificate Programme on

MLOps - Scalable ML Operations

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₹ 99,999/-
(Inclusive of all applicable taxes)

Limited seats only EMI options available

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About the programme

about

Machine Learning Operations (MLOps) is a set of practices that automates and simplifies the process of building, deploying, and maintaining Machine Learning (ML) models. It essentially bridges the gap between the development (Dev) phase of creating a Machine Learning model and the Operations (Ops) phase of getting it to run smoothly in the real world.

Learners will acquire and master the basics of MLOps skills with the help of industry and academic experts through live lectures and various hands-on tools required for the industry use cases. This programme will be a combination of practical learning (hands-on and experiential learning paradigms) and theoretical learning (live lectures). MLOps focusses on automating the entire workflow of building a ML model, including data collection, training, testing, deployment, monitoring, and retraining. This ensures a consistent and an efficient process.

As per the key market insights report by Fortune Business, the global MLOps market size was valued at US$ 720.0 million in 2022 and is projected to grow from US$ 1,064.4 million in 2023 to US$ 13,321.8 million by 2030, exhibiting a CAGR of 43.5% during the forecast period.

about

Learners will develop the following skills by the end of the programme:

  • Understand the Machine Learning (ML) lifecycle
  • Automate ML Workflow
  • Gain an understanding of DevOps principles which includes concepts like version control, continuous integration/delivery, and infrastructure management
  • Acquire the ability to collaborate with different stakeholders to achieve successful model deployment
  • Monitor and Model Governance

Learning Outcomes

What you learn

Develop hands-on expertise in

Experiment Tracking and Model Metadata

MLflow/Comet ML

Orchestration and Workflow Pipelines

Prefect / Metaflow / Kedro

Data and Pipeline Versioning

Data Version Control (DVC)/lakeFS

Feature Stores

Feast/Featureform

Model Deployment and Serving

Cloud-based MLOps Solutions (AWS SageMaker/Azure ML/Google Cloud AI Platform)

The field generates a variety of job roles, including but not limited to:

The field generates a variety of job roles, including but not limited to:

Machine Learning Operations (MLOps) Engineer

Machine Learning Engineer

Data Engineer

Data Analyst

Big Data Engineer

Data Scientist

Certificate programme recommended for

Final Year Students and Freshers

Freshers/individuals pursuing Bachelor's/Master's degree, who aspire for a career in the field of AI-ML

Working Professionals

Junior and mid-career professionals, looking for an accelerated career growth and salary hike

Prerequisites

Understanding the Fundamentals of AI and ML with basic programming and mathematical knowledge. Recommended to complete the 'Introduction to Python Programming, Statistics Fundamentals and Introduction to Scala' before the live lectures

Key highlights

120 hours of overall experiential learning

Modular Quiz, Industry Case Studies, Capstone Project, Campus Immersion

Discussion Room Community

Live doubt solving sessions by the experts

Opportunities to interact and learn from the IITM Pravartak SMEs and Domain experts from the Industry

Get access to public datasets, tutorials, coding assignments, presentations and class notes

Eligible students to appear for TCS iON NPT Assessment and get excellent career opportunities

2 days of Campus Immersion (Tentative)

Programme pedagogy

Expert-led live sessions

Get trained by the eminent professors of IITM Pravartak and Industry experts

Recorded session videos

Learn anytime, anywhere and on any device

Industry use cases

Get an understanding of real-world problems and solutions through use cases

Peer networking and expert connect

Improve learning network and ask queries to the experts through communities

Enriched with hands-on sessions

Learners will get ample scope of hands-on learning with real-world content and public datasets

Live doubt solving sessions

Get your queries answered by the experts during live classes

Digital certificate

learners to receive a digital certificate upon successful completion of the programme

Campus Immersion programme

Learners to experience a 2 day Campus Immersion during the programme *(Travel and accommodation to be borne by the learners)

Dedicated helpdesk

Get your queries resolved by connecting with our dedicated helpdesk

Programme Syllabus Overview

This comprehensive syllabus will be delivered through a combination of live lectures, recorded session videos, community-based digital classrooms as applicable.

  • Self-paced Learning: Python Programming - Programming Essentials, Data Types, Control Structures, Functions, Modules, OO Concepts, Regex using Python
  • Self-paced Learning: Data Operations and Analysis: Data Analysis: NumPy, Data Visualization: Matplotlib, Seaborn, Pandas: Data cleaning, munging/wrangling, manipulation, EDA, Working with different data sources and structures, HPO (Hyperparameter Optimization) Tuning
  • Self-paced Learning: Statistics, Descriptive statistics and Sampling techniques
  • Self-paced Learning: Programming using Scala: Programming fundamentals using Scala2, Concepts of Parallel Programming using Scala
  • Essentials of Apache Spark: Spark Architecture, DataFrame basics, DataFrame transformation and execution, DataFrame joining, Implementation using PySpark/Scala Spark
  • Ingesting Data into Spark, Spark SQL, Spark Data and Stream processing, Implementation using PySpark/Scala Spark
  • Introduction to Git and GitHub: Introduction to the Git control system, discovering collaborative work on Git and GitHub, Management of Git projects with the repository system, File and project sharing with the push function, Updating your local repository with the pull, Participation in the improvement of public projects. Introduction to workflows and their automation with GitHub Actions

  • Predictive Modeling: Regression and Classification Algorithms, Supervised and Unsupervised Algorithms, Performance Measures and Metrics
  • Convolutional Neural Networks, Pre-trained CNNs: Feature Extraction and Fine Tuning, Sequence Models - RNN, LSTM, Autoencoder, BART or T5, Attention Mechanism; Generative Adversarial Networks; Transformers Architecture
  • NVIDIA Tool Kit and GPU-based Operations
  • Implementation of ML Algorithms using Python-centric Libraries and Spark ML

  • MLOps Vs. DevOps
  • ML Project Life Cycle
  • ML Production Infrastructure
  • ML Data Processing Life Cycle with Data Storage

  • Review of Operating System Concepts
  • Basic Principles of Containerization
  • Applying CI/CD Concepts in Data Pipelines
  • Introduction to Docker
  • Dockerfiles, Images, and Containers
  • Docker Networking
  • Docker Compose
  • Orchestration
  • DataOps Orchestration and Scalability
  • Introduction to Kubernetes
  • Distributed Spark Architecture
  • Spark Resilient Distributed Datasets (RDD) and its Operations
  • Introduction to Airflow Concepts, Presentation of the Principles of Orchestration and their Utility, Directed Acyclic Graphs (DAG) Operators, Task Management through Specific Operators, Monitoring of DAG via the Airflow Graphical Interface

  • Pipelines for Model Building
  • Model Resource Management Techniques, High-Performance Modeling, Model Analysis, Model Interpretability
  • Pipelines for Real-time ML Inferencing
  • Implementation of MLOps using Cloud Services
  • Using MLflow for modeling MLOps - MLflow Tracking, MLflow Projects, MLflow Models, MLflow Registry

  • Model Deployment Strategies, Model-in-Service Deployment, Model-as-Service Deployment, Model Containerization, CICD Integration
  • Model Monitoring, Data Drift, Concept Drift
  • Scaling ML Workloads with Cloud Infrastructure
  • End-to-End Deployment - Amazon SageMaker, Amazon S3, AWS CodeBuild, AWS CodeCommit, SageMaker Training Job, SageMaker Endpoint, Amazon API Gateway, SageMaker Model Monitoring, HPO using SageMaker, CloudWatch Synthetics, CloudWatch Alarm

    • Programme Brochure

    Details about the programme and the sessions are available in the brochure.

    .

    Digital Certificate

    Learners will be awarded a co-branded digital certificate upon successful completion of the programme.

    Certificate

    Meet the Mentor(s)

    Madhusudhanan, has a PhD in AI-ML and is working towards a Post-Doctoral in the field of Large Language Models with 31 years of experience in business and technical aspects of product development from the discovery/innovation stage to product launch. + Read More

    Alok Tripathi

    Madhusudhanan ("Madhu") Baskaran

    Principal Consultant - IIT Madras Pravartak | Adjunct Faculty - IIT Madras | Translational Researcher | Co Founder - TriniPI | Imaging | LLM | AIML | Mentor|
    IIT Madras Pravartak
    Academic Expert

    Debashis Roy is a domain consultant at Tata Consultancy Services. He has completed his M.E. (Software Engineering) from Jadavpur University, Kolkata. He has been working with the Tata Group of Companies for 18+ years as a Subject Matter Expert + Read More

    Dr. Tarachand Amgoth

    Debashis Roy

    Domain Consultant,
    Tata Consultancy Services
    Industry Expert

    Dr. Himdweep Walia has been working in Higher Education domain for almost two decades now. Currently, she is working at TCS as a Subject Matter Expert (SME) and Domain Expert - Learning Programmes, Higher Education, having end-to-end ownership of learning products in the AI/ML domain. + Read More

    Dr. Tarachand Amgoth

    Dr. Himdweep Walia

    Domain Consultant
    Tata Consultancy Services
    Industry Expert

    Contact Us

    For queries, feedback & assistance

    Request a Callback

    FAQs

    Please take a look at the most frequently asked questions; you might have your query answered here.

    Undergraduates, postgraduates and working professionals with limited work experience, along with a foundational understanding of AI ML with basic programming and mathematical knowledge can apply for this programme.
    • Click on the 'Buy Now' button.
    • Login with your TCS iON Digital Learning Hub credentials or sign up as a new user.
    • After login/sign up, you will be asked to share your details required to complete your purchase. This includes your name, email ID, phone number and other details.
    • In case of 'Buy Now': On successful submission of the form, you need to proceed to make the payment by clicking on 'Click to Pay/Activate Code'. EMI options are available.
    • In case of 'Activate Now': Enter the Licence Code on the pop-up window and click the 'Activate' button. Provide your details such as name, email ID, phone number and other details required to complete the application form. Once the activation code and your details are successfully submitted, click 'Get Started/Launch' and you can view the purchased variant in 'My Dashboard'.
    • You will receive a successful purchase message on your registered email ID/mobile number.
    Note: 'Activate Now'/'Activate Code' is only applicable for institutional or bulk purchase.
    This certificate programme is envisaged to help build a strong foundation across various streams through live and recorded lectures, hands-on implementation through industry use cases and mentorship of renowned industry and IITM Pravartak SMEs. Learners will also get an opportunity to showcase their skills to potential recruiters. The entire course is being delivered by the IITM Pravartak SMEs and TCS iON Industry Experts.
    View All
    This is a one of a kind programme that brings to you best in class experts from IITM Pravartak and TCS iON. This programme will be a combination of practical learning (hands-on and experiential learning paradigms) and theoretical learning (live lectures). This course focusses on automating the entire workflow of building a ML model, including data collection, training, testing, deployment, monitoring, and retraining. The price offered is most competitive, comparable to similar products available in the market. This is a great value add to the learners.
      In case a learner misses a live lecture, he/she will be provided access under Live Lecture learning component, to view the recorded version of the session within and for a specified time frame.
    The learners would need the following infrastructure to access the learning platform:
      1. Device: A standard Desktop/Laptop with camera and mic having standard configurations with at least 8 GM RAM and standard SSD/HDD hard drive, having latest Windows/Ubuntu/RHEL as OS
      2. Internet: A regular broadband/Wi-Fi connection or a minimum mobile 4G/5G connection
      3. Cloud Infrastructure: Students need to have/create their own AWS account. This would be required for hands-On activities related to Amazon SageMaker
    Yes, all eligible learners will get an opportunity to appear in 3 job interviews basis their TCS iON National Proficiency Test (TCS iON NPT) score.
      1. Learners can appear for TCS iON NPT as per the course topic and TCS iON NPT schedule.
      2. TCS iON NPT has to be completed within 3 months from completion of the course.
    The duration of this programme is six months across the span of 24 weeks, including hands-on and doubt clearing sessions. This programme will include around 3-4 hours of live lectures to be attended by the learners each week. The live lectures are planned almost every Saturday/Sunday for around 3-4 hours. In case a learner misses a live lecture, he/she will be provided access under Live Lecture learning component, to view the recorded version of the session within and for a specified time frame.
      Minimum 70% of lecture attendance is required. Also, all the participants must secure passing marks in the quiz and project to obtain a Certificate of Completion. If not, a Certificate of Participation will be awarded to the candidates.
    Sr.No. Components Total No. Minimum Criteria Certificate Type
    1 Quiz 6 (i) 50% and above in each quiz and
    (ii) Overall 50% in 6 quizzes    		 Certificate of Completion
    2 Project 1 Overall 50% and above Certificate of Completion

      If either of the above minimum criteria is not met, then a Certificate of Participation will be awarded.
      Please note that the course fees is not refundable under any circumstances. Also, the course fee is not transferable for any other course on the TCS iON platform or for any other purpose. We will be with you at every step for your upskilling and professional growth needs.
      The softwares used for Hands-on will be mostly open source/freeware tools. Students will be required to configure the softwares on their personal machines/cloud environments. Installation and configuration guidelines will be provided. Students will have to to create a free AWS cloud account for some part of the hands-on.
      Yes. We do have an EMI option for this course.