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Machine Learning Course in Bangalore with Python

Intellipaat Machine Learning course in Bangalore will help you be a master in the concepts and techniques of Machine Learning with Python, which include ML algorithms, supervised and unsupervised learning, probability, statistics, decision tree, random forest, linear and logistic regression through real-world hands-on projects. Get the best online machine learning course training in bangalore from top data scientists.

Key Features

  • Instructor Led Training : 32 Hrs
  • Self-paced Videos : 32 Hrs
  • Exercises & Project Work : 64 Hrs
  • Certification and Job Assistance
  • Flexible Schedule
  • Lifetime free upgrade
  • 24 x 7 Lifetime Support & Access

About Machine Learning Course

Intellipaat is one of the renowned names in the domain of e-learning, offering you the most comprehensive and career-oriented Machine Learning with Python training course in and around Bangalore, India. Learners will be getting in-depth knowledge and expertise in the highly coveted concepts of Python Programming such as supervised and unsupervised learning, probability, statistics, decision tree, random forest, linear and logistic regression, and a lot more through this training. Successfully completing this training course will equip you with the skill sets related to Statistics, Time Series, and different classes of Machine Learning algorithms

What will you learn in this best Machine Learning training course in Bangalore?

  1. Basics of using data to train machines
  2. Artificial neural network concepts
  3. Multiple variables in linear regression using Python
  4. Classifying data in logistic regression using Python
  5. K-Nearest Neighbor algorithms
  6. Data Modeling
  7. Decision Tree Classifier

Who should take up this Machine Learning Course with Python?

  • Software Professionals looking for a career switch and fresh graduates
  • Professionals in Analytics, Data Science, E-commerce, and Search Engine domains

What are the prerequisites for taking up this Machine Learning online training course?

We don’t expect any prior knowledge from your side. However, a basic knowledge of programming language can be helpful.

What are the Machine Learning job opportunities in Bangalore?

The average salary of a Machine Learning Engineer in Bangalore, Karnataka, is Rs.1,095,796. per year – PayScale

Bangalore is the hub of some of the best IT companies, and due to this the demand for Machine Learning professionals is at an all-time high. This combined with the number of startups mushrooming in the Silicon Valley of India clarifies that the future for Machine Learning Engineers can only get better in this city.

What is the Machine Learning with Python market trend in Bangalore?

Machine Learning market trend in Bangalore is growing at a rapid rate. The growth of technology in this city has made marketers compare it with the Silicon Valley of the USA. The focus of multinational firms on this city has created a huge competition which can be managed by analyzing the market conditions. Machine Learning with Python Programming serves this purpose, and hence aspirants wanting to become successful Machine Learning Engineers can clearly benefit from the course and grab lucrative jobs in this city.

Why should you take up this Machine Learning using Python course online?

Machine Learning is one of the most exciting and attractive fields to get into. Being used for self-driving vehicles or for search engines like Google, Machine Learning is extensively used for making our lives simple. Intellipaat’s Machine Learning with R course emphasizes on providing hands-on experience through assignments and a real-time project that have wide implications in various industries.

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Machine Learning Course Content

Python Environment Setup and Essentials

Introduction to Python Language, features, the advantages of Python over other programming languages, Python installation, Windows, Mac & Linux distribution for Anaconda Python, deploying Python IDE, basic Python commands, data types, variables, keywords and more.

Python Language Basic Constructs

Built-in data types in Python, tabs and spaces indentation, code comment Pound # character, variables and names, Python built-in data types, Numeric, int, float, complex, list tuple, set dict, containers, text sequence, exceptions, instances,  classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug, basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise, loop and control statements, while, for, if, break, else, continue.

NumPy for Mathematical Computing

Introduction to NumPy arrays and matrices, indexing of Numpy array, datatypes, broadcasting of array math, standard deviation, conditional probability, correlation, and covariance.

Hands-on Exercise – How to import NumPy module, creating an array using ND-array, calculating standard deviation on an array of numbers, calculating the correlation between two variables.

SciPy for Scientific Computing

Introduction to SciPy and its functions, building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, SciPy with Bayes Theorem.

Hands-on Exercise – Importing of SciPy, applying the Bayes theorem on the given dataset.

Pandas for Data Analysis

Introduction to Python dataframes, importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe, various data operations like selecting, filtering, sorting, viewing, joining, combining, how to handle missing values, time series analysis, linear regression.

Hands-on Exercise – working on importing data from JSON files, selecting record by a group, applying filter on top, viewing records, analyzing with linear regression, and creation of time series.

Introduction to Machine Learning

Need of Machine Learning, Introduction to Machine Learning, Types of Machine Learning – Supervised, Unsupervised and Re-inforcement Learning. Why Machine Learning with Python. Applications of Machine Learning

Supervised Learning and Linear Regression

Introduction to supervised learning, Types of Supervised Learning – Regression &  Classification, Introduction to Regression, Simple Linear Regression, Multiple Linear Regression, Assumptions in Linear Regression, Math behind Linear Regression

Hands-on Exercise – Implementing linear regression from scratch with python. Using Python library Scikit-Learn to perform simple linear regression and multiple linear regression. Implement train-test split and predict the values on the test set.

Classification and Logistic Regression

Introduction to Classification, Linear regression vs Logistic Regression, Math behind Logistic Regression, detailed formulas, logit function and odds,  confusion matrix and Accuracy, true positive rate, false positive rate,  Threshold evaluation with ROCR.

Hands-on Exercise – Implementing logistic regression from scratch with python. Using Python library Scikit-Learn to perform simple logistic regression and multiple logistic regression. Building a confusion matrix, to find out the accuracy, true positive rate, and false positive rate.

Decision Tree and Random Forest

Introduction to tree-based classification, Understanding Decision Tree,  Impurity Function – Entropy, understand the concept of information gain for right split of node, Impurity Function – Information gain, understand the concept of information gain for right split of node, Impurity Function – Gini index, understand the concept of Gini Index for right split of node, overfitting & pruning, pre-pruning, post-pruning, cost-complexity pruning, Introduction to ensemble techniques, Understanding Bagging, Introduction to Random Forest, Finding the right number of trees in Random Forest.

Hands-on Exercise – Implementing decision tree from scratch in Python. Using Python library Scikit-Learn to build a decision tree and random forest. Visualizing the tree and changing the hyperparameters in the random forest.

Naïve Bayes and Support Vector Machine

Introduction to probabilistic classifiers, Understanding Naïve Bayes, Math behind Bayes theorem, Understanding Support Vector Machine, Kernel Functions in Support Vector Machine, Math behind svm.

Hands-on Exercise – Using Python library Scikit-Learn to build Naïve Bayes Classifier and Support Vector Classifier.

Unsupervised Learning

Types of Unsupervised Learning- Clustering and Dimensionality Reduction. Types of clustering, introduction to k-means clustering, the math behind k-means, Dimensionality reduction with PCA.

Hands-on Exercise – Using Python library Scikit-Learn to implement K-means clustering. Implementing PCA on top of a dataset.

Introduction to Deep Learning

Introduction to deep learning with neural networks, Biological neural network vs Artificial neural network, Understanding perceptron learning algorithm, introduction to deep learning frameworks, TensorFlow-Constants, Variables and Place-holders

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Machine Learning Projects

What projects I will be working in this Machine Learning certification course?

Project 1: Customer Churn Classification

Topics: This is a real-world project that gives you hands-on experience in working with most of the machine learning algorithms. The main components of the project include the following:

  • Manipulating data to extract meaningful insights
  • Visualizing data to find patterns among different factors
  • Implementing these algorithms – linear regression, decision tree, naïve Bayes

Project 2: Recommendation for Movie, Summary

Topics: This is a real-world project that gives you hands-on experience in working with a movie recommender system. Depending on what movies are liked by a particular user, you will be in a position to provide data-driven recommendations. This project involves understanding recommender systems, information filtering, predicting ‘rating’, learning about user ‘preference’ and so on. You will exclusively work on data related to user details, movie details, and others. The main components of the project include the following:

  • Recommendation for movie
  • Two Types of Predictions – Rating Prediction, Item Prediction
  • Important Approaches: Memory-Based and Model-Based
  • Knowing User Based Methods in K-Nearest Neighbor
  • Understanding Item Based Method
  • Matrix Factorization
  • Decomposition of Singular Value
  • Data Science Project discussion
  • Collaboration Filtering
  • Business Variables Overview
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Sample Machine Learning Video Tutorials

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Machine Learning Certification

This course is designed for clearing Intellipaat Machine Learning with Python Certification Exam. The entire Machine Learning with Python training course content is designed by industry professionals to get the best jobs in top MNCs. As part of this training, you will be working on real-time projects and assignments that have immense implications in the real-world industry scenarios, thus helping you fast-track your career effortlessly.

At the end of this Machine Learning with Python training program, there will be quizzes that perfectly reflect the type of questions asked in the certification exam and help you score better.

Intellipaat Course Completion Certification will be awarded upon the completion of the project work (after expert review) and upon scoring of at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.

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Machine Learning Training Reviews

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  1. Profile photo of Raghavendra Narayan Raghavendra Narayan 

    Best Machine Learning course

    I really liked the way Intellipaat approached such a complex topic like machine learning and made it so easy to understand. 5 stars to Intellipaat!

  2. Profile photo of Rashi G Rashi G 

    Machine Learning training by industry experts

    The Intellipaat trainer for machine learning came with very good experience and thus I was able to learn this technology effortlessly. Thank you Intellipaat!

  3. Profile photo of Bharat Rathore Bharat Rathore 

    Great content by Intellipaat

    The machine learning course material was very good with lots of real world examples of this awesome technology. Learning with Intellipaat was a great experience!

Machine Learning Course Advisor

Suresh Paritala

A Senior Software Architect at NextGen Healthcare who has previously worked with IBM Corporation, Suresh Paritala has worked on Big Data, Data Science, Advanced Analytics, Internet of Things and Azure, along with AI domains like Machine Learning and Deep Learning. He has successfully implemented high-impact projects in major corporations around the world.


Samanth Reddy

A renowned Data Scientist who has worked with Google and is currently working at ASCAP, Samanth Reddy has a proven ability to develop Data Science strategies that have a high impact on the revenues of various organizations. He comes with strong Data Science expertise and has created decisive Data Science strategies for Fortune 500 corporations.


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Frequently Asked Questions on Machine Learning

Why Should I Learn Machine Learning with Python from Intellipaat?

Intellipaat offers comprehensive training in Machine Learning with Python through hands-on real-world projects and case studies. As part of the training, you will learn about Machine Learning with Python algorithms, classification techniques, linear and logistic regression, supervised and unsupervised learning and more. Upon the successful completion of the training, you will be awarded with Intellipaat Machine Learning Certification.

As part of this online Machine Learning course, you will be working on real-time Machine Learning projects and step-by-step assignments that have high relevance in the corporate world, and the curriculum of this course designed by industry experts. Upon completion of the online course, you can apply for some of the best jobs in top MNCs around the world at top salaries. Intellipaat offers lifetime access to videos, course materials, 24/7 support, and course material upgrading to the latest version at no extra fee. Hence, it is clearly a one-time investment.

What are the different modes of training that Intellipaat provides?
At Intellipaat you can enroll either for the instructor-led online training or self-paced training. Apart from this Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience and they have been actively working as consultants in the same domain making them subject matter experts. Go through the sample videos to check the quality of the trainers.
Can I request for a support session if I need to better understand the topics?
Intellipaat is offering the 24/7 query resolution and you can raise a ticket with the dedicated support team anytime. You can avail the email support for all your queries. In the event of your query not getting resolved through email we can also arrange one-to-one sessions with the trainers. You would be glad to know that you can contact Intellipaat support even after completion of the training. We also do not put a limit on the number of tickets you can raise when it comes to query resolution and doubt clearance.
Can you explain the benefits of the Intellipaat self-paced training?
Intellipaat offers the self-paced training to those who want to learn at their own pace. This training also affords you the benefit of query resolution through email, one-on-one sessions with trainers, round the clock support and access to the learning modules or LMS for lifetime. Also you get the latest version of the course material at no added cost. The Intellipaat self-paced training is 75% lesser priced compared to the online instructor-led training. If you face any problems while learning we can always arrange a virtual live class with the trainers as well.
What kind of projects are included as part of the training?
Intellipaat is offering you the most updated, relevant and high value real-world projects as part of the training program. This way you can implement the learning that you have acquired in a real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning and practical knowledge thus making you completely industry-ready. You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. Upon successful completion of the projects your skills will be considered equal to six months of rigorous industry experience.
Does Intellipaat offer job assistance?
Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this we are exclusively tied-up with over 80 top MNCs from around the world. This way you can be placed in outstanding organizations like Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation part as well.
Is it possible to switch from self-paced training to instructor-led training?
You can definitely make the switch from self-paced to online instructor-led training by simply paying the extra amount and joining the next batch of the training which shall be notified to you specifically.
How are Intellipaat verified certificates awarded?
Once you complete the Intellipaat training program along with all the real-world projects, quizzes and assignments and upon scoring at least 60% marks in the qualifying exam; you will be awarded the Intellipaat verified certification. This certificate is very well recognized in Intellipaat affiliate organizations which include over 80 top MNCs from around the world which are also part of the Fortune 500 list of companies.
Will The Job Assistance Program Guarantee Me A Job?
In our Job Assistance program we will be helping you land in your dream job by sharing your resume to potential recruiters and assisting you with resume building, preparing you for interview questions. Intellipaat training should not be regarded either as a job placement service or as a guarantee for employment as the entire employment process will take part between the learner and the recruiter companies directly and the final selection is always dependent on the recruiter.
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