Master the Art of Deploying and Managing Machine Learning Models
Why Enroll in the LearnAI MLOps Course?
In the fast-evolving world of Machine Learning, MLOps (Machine Learning Operations) has emerged as a crucial discipline to streamline the deployment, management, and monitoring of ML models in production environments. MLOps ensures that models are not only accurate but also scalable, reliable, and continuously optimized to meet the demands of real-world applications. At LearnAi, our MLOps course is designed to equip you with the skills and knowledge needed to bridge the gap between data science and software engineering, enabling you to deploy and manage ML systems effectively.
Located in Dilsukhnagar, Hyderabad, LearnAi provides a comprehensive MLOps curriculum that covers essential concepts such as version control, model deployment, continuous integration and delivery (CI/CD) for ML, monitoring, and collaboration between data scientists and IT teams. Whether you're looking to enhance your current skill set or shift your career into the growing field of MLOps, this course is tailored to provide practical insights and hands-on experience with industry-standard tools and platforms.
The LearnAi MLOps course is ideal for anyone aiming to enhance their skills in deploying and managing ML models in production. This course is suitable for:
Machine Learning Engineers
Professionals who want to master the process of operationalizing ML models and deploying them in real-world applications.
Data Scientists
Data scientists who want to take their models from development to production and ensure their models continue to perform reliably.
Software Engineers
Developers interested in learning how to integrate machine learning into production-level applications and infrastructure.
DevOps Engineers
DevOps professionals looking to expand their expertise into the MLOps domain to support the deployment and maintenance of ML systems.
DevOps Course Curriculum
The DevOps Course follows a comprehensive and systematic curriculum. It includes the following core modules:
Fundamentals in C
Program
Programming
Programming Languages
Types of Software
Introduction to C
History of C
Features of C
Applications of C
Character Set, ASCII Table
Tokens
Keywords
Identifiers & Naming Rules
Constants
Data Types
Type Qualifiers
How Data is Stored in Computer Memory
Variables
Variable Declaration
Variable Assignment
Variable Initialization
Comments
Defining Constants
Input-Output Functions
Input-Output Library Functions
Non-Formatted Input and Output
Character-Oriented Library Functions
Compiler, Linker, and Loader
Program Execution Phases
Formatted Library Functions
Mathematical Library Functions
Structure of a C Program
IDE
Basic Programs
Arrays
Arrays
One-Dimensional Arrays
Declaration of 1D Arrays
Initialization of 1D Arrays
Accessing Elements of 1D Arrays
Reading and Displaying Elements
Programs on 1D Arrays
Two-Dimensional Arrays
Declaration of 2D Arrays
Initialization of 2D Arrays
Accessing Elements of 2D Arrays
Reading and Displaying Elements
Programs on 2D Arrays
Three-Dimensional Arrays
Pointers
Understanding Memory Addresses
Pointer Operators
Pointer
Pointer Advantages and Disadvantages
Declaration of Pointer Variables
Initialization of Pointer Variables
Dereferencing / Redirecting Pointer Variables
Declaration versus Redirection
Void Pointer
Null Pointer
Compatibility
Array of Pointers
Pointer to Pointer
Pointer Arithmetic
Dynamic Memory Allocation Functions
Storage Classes
Object Attributes
Scope
Extent
Linkage
auto
static
extern
register
Structures, Unions, Enumerations and Typedef
Structures
Structure Type Declaration
Structure Variable Declaration
Initialization of Structure
Accessing the Members of a Structure
Programs Using Structures
Operations on Structures (Copying and Comparing Structures)
Nested Structures (Complex Structures)
Structures Containing Arrays (Complex Structures)
Array of Structures (Complex Structures)
Pointer to Structure
Accessing Structure Member through Pointer Using Dynamic Memory Allocation
Pointers within Structures
Self-Referential Structures
Passing Structures to Functions
Functions Returning Structures
Unions
Differences between Structures & Unions
Enumerated Types / enum Keyword
The Type Definition / typedef Keyword
Bit Fields
Operators and Expressions
Arithmetic Operators
Arithmetic Expressions
Evaluation of Expressions
Relational Operators
Logical Operators
Assignment Operators
Increment & Decrement Operators
Conditional Operator
Bitwise Operators
Type Casting
Sizeof Operator
Comma Operator
Operators Precedence and Associativity
Expressions
Evaluation of Expressions
Control Statements
Conditional Control Statements
if
if-else
Nested if-else
if-else-if Ladder
Multiple Branching Control Structure
switch-case
Loop Control Statements
while
do-while
for
Nested Loops
Jump Control Structures
break
continue
goto
return
Programs
Strings
String Concept
Introduction to Strings in C
Storing Strings
The String Delimiter
String Literals (String Constants)
Strings and Characters
Declaring Strings
Initializing Strings
Strings and the Assignment Operator
String Input Functions / Reading Strings
String Output Functions / Writing Strings
String Input-Output using fscanf() and fprintf() Functions
Single Character Library Functions / Character Manipulation in Strings
String Manipulation Library Functions
Programs Using Character Arrays
Array of Strings (2D Character Arrays)
Programs Using Array of Strings
Functions
Functions
Advantages of Using Functions
Defining a Function
Calling a Function
Return Statement
Function Prototype
Basic Function Designs
Programs Using Functions
Scope
Recursion
Iteration vs Recursion
Nested Functions
Variable Length Number of Arguments
Parameter Passing Techniques – Call by Value & Call by Address
Functions Returning Pointers
Pointers and One-Dimensional Arrays
Pointers and Two-Dimensional Arrays
Passing 1D Arrays to Functions
Passing 2D Arrays to Functions
Pointers and Strings
Passing Strings to Functions
Pointer to Function
Preprocessor Directives
The #include Preprocessor Directive & User Defined Header Files
The #define Preprocessor Directive: Symbolic Constants
The #define Preprocessor Directive: Macros
Conditional Compilation Directives
#if
#else
#elif
#endif
#ifdef
#ifndef
#undef
#error
#line
#pragma
Course Overview
The LearnAi MLOps course offers a structured, hands-on learning experience to ensure that participants gain the practical knowledge required to deploy, monitor, and maintain machine learning models. The curriculum focuses on real-world applications, enabling you to gain experience with the tools, platforms, and best practices used by top organizations in the industry.
Skills You Will Gain
By the end of the LearnAi MLOps course, you will acquire the following skills:
Model Deployment Expertise
Learn how to deploy machine learning models efficiently and securely in various environments.
CI/CD Implementation for ML
Automate your machine learning workflows with continuous integration and continuous delivery pipelines.
Model Monitoring and Maintenance
Track and maintain models to ensure their ongoing effectiveness and accuracy in production.
Version Control for Machine Learning
Implement version control techniques for both code and models, ensuring reproducibility and traceability.
Collaboration in MLOps
Develop the skills to work effectively in multidisciplinary teams to streamline ML workflows and operations.
Learn MLOps Course from beginners to advanced in Three Phases
The LearnAi MLOps course is divided into three key phases to provide a structured and comprehensive learning journey:
1. Exploration
Industrial Standard Course Structure
Job Oriented Programs
Domain Expertise Trainers
Recording Sessions
24/7 Portal Access
1 to 1 Mentorship
2. Understanding
Doubt Sessions
Daily Assignments
Weekly Test
Project Explanations
Project Implementation
Course Completion Certifications
3. Achievement
Resume Preparations
Interview Preparation
Mock Interviews
Internships Oppurtunity
Resume Marketing
100% Job Assistance
Tools and Technologies
• Kubeflow • MLflow • AWS SageMaker • Google AI Platform • Azure Machine Learning • Docker • Kubernetes • Jenkins • Git and DVC (Data Version Control) • Terraform • Prometheus and Grafana
Job Roles
• MLOps Engineer • Machine Learning Engineer • Data Engineer • DevOps Engineer (with MLOps expertise) • AI/ML System Architect • Cloud Engineer (with MLOps focus) • Model Deployment Engineer • Data Scientist (with MLOps specialization)
Enroll in the LearnAi MLOps course today to advance your career in the exciting field of machine learning operations and start building scalable, reliable ML systems!
FAQs
What is C programming?
C is a high-level programming language known for its efficiency and control over hardware, widely used in system and application software development.
What are the main features of C programming?
C is praised for its simplicity, portability, efficiency, and capability for direct memory manipulation.
What are pointers in C, and why are they important?
Pointers are variables that store memory addresses, essential for dynamic memory management and efficient data handling.
How does C differ from C++?
C is a procedural language focused on functions, while C++ extends C with object-oriented features like classes and inheritance for more complex programming.
What makes LearnAI courses exceptional?
Our courses feature cutting-edge curricula, expert instructors, and hands-on projects that provide practical experience and real-world applicability.
How qualified are LearnAI instructors?
Our instructors are experienced professionals with extensive industry backgrounds, offering valuable insights and skills.
What kind of support do students receive?
Students benefit from personalized mentorship, detailed feedback, and extensive support throughout their learning process.
How does LearnAI support career growth?
We offer career services including resume building, interview coaching, and job placement assistance to help you advance in your career.li>
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For upcoming MLOps Course in Dilsukhnagar call @ + 91 939 002 3585
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