MACHINE LEARNING training course in

Machine Learning

Machine learning is systematic learning approach to give ability to the computer programs to ‘learn’ with Data. There are many methods and ways to learn machine learning. Learning ‘ML’ require us to understand Python, R and other tools such TensorFlow. We would use an incremental way to learn ML. The classes are designed in accordance to the latest industry standards and are backed by lab practicals.

45 HOURS

7 LESSONS

15 STUDENTS

Price: ₹ 15,000

Upcoming Batches

Offline
Date & Time
Course Fee
₹15,000 (all inclusive)
Online
Date & Time
Course Fee
₹10,500 (all inclusive)

Career Prospects

Career Opportunity

Career Opportunity

2 Million of professionals associated with python Software Developer across the globe

Salary Trend

$90,300 is the median advertised salary for Full Stack Developer in 2017. Companies competing to hire the limited number of python Developer willing to offer up to US $300,000 per year. (Indeed.com & Dice.com)

Training Journey

Training Journey

Course Description

ML course is designed in keeping the needs of the industry and classes will be taken by industry experts. Machine Learning is engine behind the facial recognition to fraud detection and driverless car. This course will help the student to learn the key concepts of Machine learning such as, automatic analyzation of large data set. Data preprocessing, Basic statistics, Regression and Classification. We would be offering free Python course with this course.

After the completion of the course you would possess skill to create supervised and unsupervised machine learning models. Gain practical knowledge and hands on. Gain deeper understanding about vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.

You would understand about Machine Learning and apply machine learning techniques in day to day life. You would be able to grasp better theoretical concepts, and would be able to model and develop models, using a wide variety of machine learning algorithms like deep learning.

CURRICULUM

  • What is Machine Learning?
  • Supervised Learning
  • Unsupervised Learning
  • Apache Mahout
  • Tensorflow
  • MLPACK
  • Installing Python
  • Execute Python program
  • Writing your first program
  • Python keywords & Identifiers
  • Python Indentation
  • Getting input output
  • Variables
  • Numbers
  • Strings
  • Lists
  • Tuple
  • Dictionary
  • Control Flow Statements
  • While loop
  • for loop
  • break & continue statement
  • pass statement
  • Calling a function
  • Function arguments
  • Built-in functions
  • Scope of variables
  • Passing function to a function
  • Decorators
  • Lambda
  • Module
  • Import a module
  • Command line arguments using sys module
  • Standard module-OS
  • Introduction about classes & objects
  • Creating a class & object
  • Inheritance
  • Methods Overriding
  • Data hiding
  • Writing data to a file
  • Reading data from a file
  • Additional file methods
  • Working with files
  • Working with Directories
  • Model Representation
  • Cost Function
  • Gradient Descent
  • Multiple Features
  • Gradient Descent For Multiple Variables
  • Features and Polynomial Regression
  • Normal Equation
  • Setting up opencv
  • Loading and displaying images
  • Applying image filters
  • Tracking faces
  • Face recognition
  • What is Hadoop?
  • MapReduce
  • File handling with Hadoop
  • Hypothesis Representation
  • Decision Boundary
  • Cost Function
  • Simplified Cost Function and Gradient Descent
  • Multiclass Classification: One-vs-all
  • Logistic regression
  • Gaussian process regression
  • Support vector machines
  • Random forests
  • Information fuzzy networks(IFN)
  • Bayesian statistics
  • Decision tree algorithms
  • Linear classifier
  • k-nearest neighbors algorithm(KNN)
  • Association rule learning algorithms such as Apriori and Eclat
  • Hierarchical clustering
  • Fuzzy clustering
  • k-means clustering
  • BIRCH
  • Anomaly detection
  • EM algorithm
  • Feature selection
  • Feature extraction
  • Principal component analysis(PCA)
  • Principal component regression(PCR)
  • Linear discriminant analysis(LDA)
  • Factor analysis
  • Multidimensional scaling(MDS)
  • The Problem of Overfitting
  • Cost Function
  • Regularized Linear Regression
  • Regularized Logistic Regression
  • Model Representation
  • Examples and Intuitions
  • Multiclass Classification
  • Cost Function
  • Backpropagation Algorithm
  • Backpropagation Intuition
  • Gradient Checking
  • Random Initialization
  • Introduction to Convolutional Neural Networks (CNN)
  • Convolutional Autoencoders
  • Deep CNN
  • Image Searching

PRACTICE ON TOOLS

Image
Image

KEY FEATURES

Instructor Led Session Classroom Sessions

All our session are backed by a classroom instructor. The sessions have equal amount of theory and practicals. Every session is backed by an question and answer session afterwards.

Practical Example Scenarios Discussion

We use real data and data streams to create machine learning models. These models are closely related to the real world and real work scenarios. We may use vision APIs, Data analysis API and TensorFlow.

Regular Assignments

After completion of every topic, students are instructed to submit assignments. These assignment promotes independent learning and helps to develop concepts.

PROJECTS

Study of pharma products

Study of World weather patterns

FAQS

College students, Working professionals, Developers, Analytical Managers, Business Analysts, Architects, Analytics Professionals, Graduates and Experienced Professionals.

We cover 2 major projects

Yes all the sessions are classroom based.

MORE ABOUT THIS COURSE

Classroom Sessions Led by Instructors

Candidates choose to acquire machine learning course in Gurgaon with us will get guidance from a large number of experts, all of whom immense knowledge via online video sessions. Along with vast knowledge and expertise related to each aspect of the course, you will get opportunity to clear your doubts from the faculties related to machine learning training in Gurgaon. We have experienced and authorized instructions to impart training to you (students) in an effortless way.

Discussions on Practical Examples and Current Scenarios

Our faculty members associated with providing you machine learning training in Gurgaon remain well versed with various ongoing strategies prevailing in the technology industry. Therefore, with the help of live project sessions, you will get opportunity to attain clear perspective related to practical implementation of any particular topic mentioned in the curriculum of the respective training course.

Assignments on a Regular Basis

You will get assignments regularly under our machine learning course in Gurgaon. These will help you boost your knowledge associated with each topic we taught to you. Our faculty members and instructors help you to prepare for interviews with outstanding resume under their supervision. Other than this, we provide a pool of placement opportunities to our students on an individual basis.

Machine Learning Training Certification

Machine learning refers to a systematic learning approach, which allows computer programs to learn with the help of available Data. For this, you will find different ways and methodologies to acquire knowledge on machine learning. Only, if you want to join machine learning course in Gurgaon and learn Machine Learning, you should possess good knowledge on a few basic tools and concepts, such as Python R and TensorFlow. Our team use incremental way to let you to gain knowledge about Machine Learning and we design each class and machine learning training in Gurgaon as per the latest industrial standards backed fully with lab practical sessions.

HIRE

FROM US!

Hire Now