Certified Machine Learning Specialist

Duration: 1464 hours + 19 days Project

Eligibility: Pass in 12 th Standard

Designations
Designations	Avg. Base Salary*
Data Scientist	INR 1011000 per annum
Data Science Analyst	INR 1000000 per annum
Data Science Engineer	INR 900000 per annum
Machine Learning Engineer	INR 752000 per annum
Machine Learning	INR 1119000 per annum
NOTE: There are umpteen types of job opportunities, designations freelancing opportunities with wide variety of payment options other than the ones mentioned in this table and it is practically not possible to list them all. The skills you earn from this program combined with the skills earned by doing projects can catapult your career into unimaginable heights.

*Salary estimates are based on salaries submitted to Glassdoor.

About CMLS

A certification by NGJ as “Certified Machine Learning Specialist” can be achieved in 3 ways.

Score of 80% in the final certification test of Certified Machine Learning Specialist.
Pass in the below mentioned certificate programs with 80% each wherein the gap between the certification of successive programs do not exceed 30 days.
- Certificate Program in Software Programming Fundamentals
- Certificate Program in Web App Development
- Certificate Program in Machine Learning and Deep Learning
Pass in the Open Certification Test for CMLS (A set of examinations and Project Works covering all the modules of the aforementioned certificate programs).

Program Framework

This is a 3-Level certification program wherein it is mandatory to pass each level to move to the next level.

Level 1 - Software Programming Fundamentals

Module 1: C Programming (144 hours + 4 days for Project)

Number System
Data Types Part 1
I/O Functions
Conditional Execution
Structure & Nesting
Functions & Prototypes
Data Types Part 2
Arrays
Pointers
C Pre-Processor & Compilation
Scope & Dynamic Memory
Other Data Types
Extensive Programming Practice
Project Work on C Programming
Module Assessment Test: The result is calculated as collective score of the test and Project Work Score

Module 2: Data Structures & Algorithms (216 hours training)

Arrays
Problems on Arrays
Linked List
Problems based on Linked List
Stacks
Problems based on Stacks
Queues
Problems based on Queues
Graphs
Problems based on Graphs
Introduction to Algorithms
Searching
Sorting
Greedy
Dynamic
Extensive Programming Practice based on Company Interview Problems
Module Assessment Test: The result is calculated as the collective score of the test and various internal assessment procedures.

Module 3: Operating System (180 hours + 7 hours Project)

Overview of Operating Systems and Functionalities
Characteristics of OS
Hardware concepts related to OS
CPU states
I/O Channels
Memory Hierarchy
Microprogramming
The Concept of a Process
Operations on Processes
Process states and Concurrent Processes
Process Control Block and Process Context
UNIX Process Control and Management
PCB, Signals, Forks and Pipes
Interrupt Processing
Operating System Organisation
OS Kernel FLIH
Dispatcher
Job and Process Scheduling
Scheduling Algorithms
Process Hierarchies
Problems of Concurrent Processes
Critical Sections, Mutual Exclusions, Synchronization and Deadlock
Mutual Exclusion
Process Co-operation
Producer and Consumer Processes
Semaphores
Use of Semaphores to implement mutex (mutual exclusion object)
Process Synchronization
Implementation of Semaphores
Critical Regions
Conditional Critical Regions
Monitors and Ada Tasks
Inter process communication (IPC)
Message Passing – Direct and Indirect
Deadlock
Memory Organisation and Management
Storage Allocation
Virtual Memory Concepts, Paging and Segmentation
Address Mapping
Virtual Storage Management
Page Replacement Strategies
File Organisation: Blocking and Buffering
File Descriptor and Directory Structure
File and Directory Structures, Blocks and Fragments
Directory Tree, inodes (index nodes), File Descriptors and UNIX File Structure
Project Work (PW): Develop an OS in class – 7hrs

Level 2 - Web App Development

Module 1: Databases + MySQL (72hrs)

Introduction to Relational Databases
Relational Design Theory
Normalization Forms
UML (Unified Modeling Language)
MySQL Foundation and Practice
Indexes
Transactions
Constraints and Triggers
Views
Authorizations
Recursion in SQL
Semi-Structured Data
12.1. XML (eXtensible Markup Language)
12.2. JSON (JavaScript Object Notation)
12.3. XPATH
12.4. Xquery (XML Query)
Practice of Designing DataBase for various applications
Module Assessment Test

Module 2: No SQL Databases (MongoDB) (72hrs)

Introduction to NoSQL Databases
Difference between RDBMS and NoSQL Databases
Pros and Cons of NoSQL Databases
Types of NoSQL Databases
Mongo Structure
Document Store
Features of MongoDB
Replication
Memory Management
Schema Designing and Modeling
Installing and working with Mongo
CRUD Operations in Mongo
Indexing and Aggregation
Module Assessment Test

Module 3: Computer Networking (144hrs)

Computer Networks
Protocols
Packets Switching
Circuit Switching
Layered Architecture
Physical Media
Encapsulation
Networks under attack
Application Layer
Web and HTTP
HTTP Message Format
Web Caching
SMTP, POP3 etc.
Transport Layer
Network Layer
Link Layer
Wireless and Mobile Networks
Security in Computer Networks
Network Management
Assessment Test

Module 4: Web App Development (PHP + HTML + CSS + JavaScript) (180 hours + 4 days Project)

PHP Development
Editors
Elements
Tags
Headings
Paragraphs
Styles
Formatting
HTML CSS
HTML Links
HTML Images
Tables
Blocks
Classes
Iframes
Forms
HTMLS
JS Operators
JS Functions
JS Data Types
JS Objects
JS Conditional Statements
JS Bitwise
JS Regex
Final Project: Web Application
Module Assessment Test

Level 3 - Machine Learning & Deep Learning

Module 1: Fundamentals of Linear Algebra (72hrs)

Systems of Linear Equations
Row Reduction and Echelon Forms
Matrix Operations, including inverses
Block Matrices
Linear Dependence and Independence
Subspaces, Bases and Dimensions
Orthogonal Bases and Orthogonal Projections
Gram-Schmidt Process
Linear Models and Least-Square Problems
Determinants and their properties
Cramer’s Rule
Eigenvalues and Eigenvectors
Diagonalization of a Matrix
Symmetric Matrices
Linear Transformations
Singular Value Decomposition
Module Assessment Test

Module 2: Statistics and Probability (72hrs)

Counting
Random Variables, Distributions, Quantities, and Mean Variance
Conditional Probability, Bayes’ theorem, and Base Rate Fallacy
Joint Distributions, Covariance, Correlation, and Independence
Central Limit Theorem
Bayesian Inference with Known Priors, and Probability Intervals
Conjugate Priors
Bayesian Inference with Unknown Priors
Frequentist Significance Tests, and Confidence Intervals
Resampling Methods: Bootstrapping
Linear Regression
Module Assessment Test

Module 3: Linux (72hrs)

Linux Foundation
Linux Filesystem Tree Layout
Processes
Signals
Package Management Systems
RPM (Red Hat Package Manager)
dpkg (package manager for Debian-based systems)
YUM (Yellowdog Updater Modified)
Zypper
APT (Advanced Package Tool)
System Monitoring
Process Monitoring
Memory Management and Usage
I/O Monitoring and Tuning
I/O Scheduling
Disk Partitioning
Version Control
Introduction and Working on Git on Linux
Module Assessment Test

Module 4: Python Programming Language with OOPs in Python (96 hours + 4 days Project)

Why Code in Python
Different Parts of the Python Program
The Python Interpreter
Data Types
Files and everything else
Python Statement and Syntax
Iterations and Comprehensions
Functions
Modules
Classes & OOPs
Exception and Tools
Project: Web Development Project using Python & HTML, JS & CSS
Module Assessment Test

Module 5: Machine Learning & Deep Learning (144hrs + 7 days Project)

Numpy
Pandas
Scikit-learn
Tensor Flow
Keras
Linear Aggression
Logistics Aggression
Trees and Ensemble Method
Neural Networks
ANN (Artificial Neural networks)
CNN (Convolutional Neural Network)
RNN (Recurrent Neural Network)
Support Vector Machines
Assessment Test
Final Project on Machine Learning up for submission

Note: Students are permitted to apply for individual certification for each Level.