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About Course:

Encourage yourself and become to master in trending Machine Learning skill. This course has been designed by highly experienced, real time working professionals & experts. In this course candidates will learn advanced and basic concepts of Machine Learning. Our experts will be going to demonstrate challenges and solutions which belong to real-world requirements. We are covering linear regression, logistic regression, Naïve Bayes, kNN, Random forest; candidate will learn both theory and implementation of these algorithms in R and python. This course provides a comprehensive overview of each & every step that you need to learn, curriculum has been designed by highly experienced working professionals based on industry requirement.

Duration : 30 hours

Fee: 299

Job Trends

Who Should Learn?
  • Any IT experienced Professional
  • Who wants to build career in machine learning
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA

Machine Learning training course does not presume or require any prior knowledge in machine learning. To understand the concepts, presentation and to complete the exercises, we are recommending that students have following:

  • Candidate should be comfortable with variables and coefficients
  • Linear equations
  • Functions & Graphs
  • And histograms
  • Proficiency in programming basics

If, Prior experience of coding in Python is beneficial.

Candidate should need to feel comfortable reading and writing Python code which contains basic programming constructs, i.e. function definitions/invocations, lists and dicts, including conditional expressions.

Delivery Methodology

We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course.

Class Delivery

Live Interactive classes with expert

Training Calender

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  • 24 hours on-demand video
  • Articles
  • Coding Exercises
  • Full lifetime access
  • Certificate of Completion


Machine Learning

What is Machine Learning?
Machine learning is a powerful tool for making highly accurate and actionable predictions about your products, customers, marketing efforts, or any number of other applications. Learning with data, use statistical technique without being explicitly program.

Why to learn Machine learning? 

  • There is a growing need among companies for professionals to know ins and outs of machine learning.
  • The machine learning market size is expected to grow USD 1.03 Billion to USD 8.81 Billion by 2022.

Acquire new skills with our Machine Learning Certifcation Training Course

  • Master in concepts of machine learning
  • Recommendation engine and time series modeling
  • Gain practical knowledge over principles, algorithms, and applications of machine learning.
  • Hands-on approach includes working on projects and hands-on exercises.
  • Thorough knowledge on statistical approach.
  • Validate machine learning models and decode various accuracy metrics. 
  • Improve in models using optimization algorithms, include Boosting & Bagging techniques.
  • Thorough knowledge on theoretical & fundamental concept & how they can relate each other with practical approach?

Course summary
In this course candidate learn how to automate data and doing analysis, how to enable computers to learn and adapt, to do specific tasks without explicit programming. Introduction to Machine learning, Artificial Intelligence and their usage in practical real world. The various theories used in modeling and tools for data and programming, types of machine learning, plotting and visualizing, statistical methods, data modeling, decision trees, clustering models, basics and real life examples of neural networks. After completion of training candidate has proficient knowledge on concepts of machine learning including supervised and unsupervised learning, algorithms, support vector machines, mathematical and heuristic aspects, and hands-on modeling to develop algorithms.

Machine Learning Certification Training Course & Curriculum

Introduction to Machine learning

  • What is machine learning?
  • History of machine learning
  • Uses of machine learning

Types of machine learning

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Transfer learning

Tools for machine learning

  • Programming languages
  • Data repositories
  • Hierarchical databases
  • Software used

Basics of Python programming

  • Installing Python
  • Matrix operations
  • Data loading/unloading
  • Plotting and visualizing
  • Algorithms - Predicting and modeling

Statistical methods

  • Graph theory
  • Probability
  • Bayes theorem
  • Regression models

Data modeling - Linear regression

  • Model representation
  • Cost function
  • Gradient descent for linear regression

Data modeling - Logistic regression

  • Hypothesis representation
  • Decision boundary

Decision trees

  • Basics of decision trees
  • Uses for decision trees
  • Advantages and limitations
  • How decision trees work

Decision trees example

  • Create a decision tree
  • Requirement
  • Training the data

Classifiers & Support vector machines

  • Classifiers
  • Support vector machines
  • Linear and non linear classification
  • What are SVM?
  • Where are SVM used?

Association rules learning

  • What is ARL?
  • Where are ASL rules used?
  • Support, Confidence, lift and conviction


  • What is clustering?
  • Where is clustering used?
  • Clustering mode

Clustering K means Model example

  • Preparing the data
  • Workbench method
  • Command-line method
  • Coded method

Basics of neural networks

  • Introduction to Neural Networks
  • Why Study Neural Networks?
  • Real life examples of neural network

Types of neural networks

  • Perception
  • Recurrent neural networks
  • Convolution neural network

Additional topics

  • Evaluating Model Performance
  • Improving Model Performance
  • Similarity between R and Python
  • Specialized Machine Learning Topics

Student Take away

  • Study Material
  • Learning stuff
  • Sample project for practice

Class Delivery

  • Live Interactive classes with expert

Delivery Methodology

  • We are using an experiential delivering methodology that blends theoretical concepts with hands-on practical learning to ensure a holistic understanding of the subject or course.

Use Case

Use Case 1


Benefits of Certificate

Certification demonstrates your dedication, motivation and technical knowledge on a specific platform. Having a certification shows that you not only possess comprehensive knowledge of that technology but you also care enough about your own career to spend the time and money to get the certification.

We are welcoming our Students or professionals to participate in our professional online courses. We are offering great variety of online training programs and professional courses that you can always find as desired. After the completion of training program they will receive a certificate from BISP. As a Certified professional you can apply that knowledge in your future profession and enjoy with better salaries & career prospects.

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