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Machine Learning Training Course in Bangalore

Intellipaat Machine Learning course in Bangalore will help you to 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 Machine Learning training in Bangalore from top data scientists.

Key Features

32 Hrs Instructor Led Training
32 Hrs Self-paced Videos
64 Hrs Project work & Exercises
Certification and Job Assistance
Flexible Schedule
Lifetime Free Upgrade
24 x 7 Lifetime Support & Access

Machine Learning Course in Bangalore Overview

Intellipaat is one of the renowned names in the domain of e-learning, offering you the most comprehensive and career-oriented Machine Learning online course in 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 ML algorithms.

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

Intellipaat, one of the premier Machine Learning Institutes in Bangalore provides a world class course on ML in which you can learn:

  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 Neighbors algorithm
  6. Data Modeling and Decision Tree Classifier.

Intellipaat’s Machine Learning Python course can be joined by:

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

We don’t expect any prior knowledge from your side. However, a basic knowledge of programming language can be helpful when joining the Machine Learning classes in Bangalore.

The average salary of an ML 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 professionals in this domain 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 ML Engineers can only get better in this city.

ML market trend in city 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. By having a Machine Learning certification, it increases the possibilities of getting employed and bagging lucrative jobs in the IT city.

Some of the reasons why you should sign up for this course are as follows:

  • There are over 2,882 Machine Learning jobs open and available in India in Indeed
  • According to LinkedIn, the average income of Machine Learning Engineers in India is about ₹600,000 per annum.

Intellipaat offers one of the best Machine Learning courses in Bangalore. This certification program is led by Machine Learning experts from leading industries in India and the US. It focuses on helping you understand the ML fundamentals such as Natural Language Processing (NLP), Python, and more. Moreover, you will work on real-world assignments and projects that will enhance your learning experience.
Advantages Of Machine Learning Course

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Course Fees

Self Paced Training

  • 32 Hrs e-learning videos
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access
$211

Online Classroom preferred

  • Everything in self-paced, plus
  • 32 Hrs of instructor-led training
  • 1:1 doubt resolution sessions
  • Attend as many batches for Lifetime
  • Flexible Schedule
  • 16 Aug
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 22 Aug
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 30 Aug
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
$351 10% OFF Expires in
$0

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 support
  • Strong Reporting

Machine Learning Course Content in Bangalore

Module 01 - Introduction to Machine Learning preview videos

1.1 Need of Machine Learning
1.2 Introduction to Machine Learning
1.3 Types of Machine Learning, such as supervised, unsupervised, and reinforcement learning, Machine Learning with Python, and the applications of Machine Learning

2.1 Introduction to supervised learning and the types of supervised learning, such as regression and classification
2.2 Introduction to regression
2.3 Simple linear regression
2.4 Multiple linear regression and assumptions in linear regression
2.5 Math behind linear regression

Hands-on Exercise:

1. Implementing linear regression from scratch with Python
2. Using Python library Scikit-Learn to perform simple linear regression and multiple linear regression
3. Implementing train–test split and predicting the values on the test set

3.1 Introduction to classification
3.2 Linear regression vs logistic regression
3.3 Math behind logistic regression, detailed formulas, the logit function and odds, confusion matrix and accuracy, true positive rate, false positive rate, and threshold evaluation with ROCR

Hands-on Exercise:

1. Implementing logistic regression from scratch with Python
2. Using Python library Scikit-Learn to perform simple logistic regression and multiple logistic regression
3. Building a confusion matrix to find out accuracy, true positive rate, and false positive rate

4.1 Introduction to tree-based classification
4.2 Understanding a decision tree, impurity function, entropy, and understanding the concept of information gain for the right split of node
4.3 Understanding the concepts of information gain, impurity function, Gini index, overfitting, pruning, pre-pruning, post-pruning, and cost-complexity pruning
4.4 Introduction to ensemble techniques, bagging, and random forests and finding out the right number of trees required in a random forest

Hands-on Exercise:

1. Implementing a decision tree from scratch in Python
2. Using Python library Scikit-Learn to build a decision tree and a random forest
3. Visualizing the tree and changing the hyper-parameters in the random forest

5.1 Introduction to probabilistic classifiers
5.2 Understanding Naïve Bayes and math behind the Bayes theorem
5.3 Understanding a support vector machine (SVM)
5.4 Kernel functions in SVM and math behind SVM

Hands-on Exercise:

1. Using Python library Scikit-Learn to build a Naïve Bayes classifier and a support vector classifier

6.1 Types of unsupervised learning, such as clustering and dimensionality reduction, and the types of clustering
6.2 Introduction to k-means clustering
6.3 Math behind k-means
6.4 Dimensionality reduction with PCA

Hands-on Exercise:

1. Using Python library Scikit-Learn to implement k-means clustering
2. Implementing PCA (principal component analysis) on top of a dataset

7.1 Introduction to Natural Language Processing (NLP)
7.2 Introduction to text mining
7.3 Importance and applications of text mining
7.4 How NPL works with text mining
7.5 Writing and reading to word files
7.6 Language Toolkit (NLTK) environment
7.7 Text mining: Its cleaning, pre-processing, and text classification

Hands-on Exercise:

1. Learning Natural Language Toolkit and NLTK Corpora
2. Reading and writing .txt files from/to a local drive
3. Reading and writing .docx files from/to a local drive

8.1 Introduction to Deep Learning with neural networks
8.2 Biological neural networks vs artificial neural networks
8.3 Understanding perception learning algorithm, introduction to Deep Learning frameworks, and TensorFlow constants, variables, and place-holders

9.1 What is time series? Its techniques and applications
9.2 Time series components
9.3 Moving average, smoothing techniques, and exponential smoothing
9.4 Univariate time series models
9.5 Multivariate time series analysis
9.6 ARIMA model and time series in Python
9.7 Sentiment analysis in Python (Twitter sentiment analysis) and text analysis

Hands-on Exercise:

1. Analyzing time series data
2. The sequence of measurements that follow a non-random order to recognize the nature of the phenomenon
3. Forecasting the future values in the series

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Machine Learning Projects and Case Studies

What projects and case studies will I be working on in this Machine Learning course Online?

Project 01: Analyzing the Trends of COVID-19 with Python

Industry: Analytics

Problem Statement: Understanding the trends of COVID-19 spread and checking if restrictions imposed by governments around the world have helped us curb COVID-19 cases and by what degree

Topics: In this project, we will use Data Science and Python and perform visualizations to better understand the data on COVID-19. We will also use time series analysis to make predictions about future cases.

Highlights:

  • Using Pandas to accumulate data from multiple data files
  • Using plotly to create interactive visualizations
  • Using Facebook’s Prophet library to make time series models
  • Visualizing the prediction by combining these technologies

Project 02: Customer Churn Classification

Topics: This is a real-world project that gives you hands-on experience in working with most of the ML algorithms.

Highlights:

  • Manipulating data to gain meaningful insights
  • Visualizing data to figure out trends and patterns among different factors
  • Implementing these algorithms: linear regression, decision tree, and Naïve Bayes

Project 03: Creating a Recommendation System for Movies

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 requires you to deeply understand information filtering, recommender systems, user ‘preference’, and more. You will exclusively work on data related to user details, movie details, and others.

Highlights:

  • Recommendation for movies
  • Two types of predictions: Rating prediction and item prediction
  • Important approaches: Memory-based and model-based
  • Knowing user-based methods in k-nearest neighbor
  • Understanding the item-based method
  • Matrix factorization
  • Decomposition of singular value
  • Data Science project discussion
  • Collaboration filtering
  • Business variables overview

Case Study 01: Decision Tree

Topics: Understand the structure of a dataset (PIMA Indians Diabetes database) and create a decision tree model based on it by using Scikit-Learn

Case Study 02: Insurance Cost Prediction (Linear Regression)

Topics: Understand the structure of a medical insurance dataset, implement both simple and multiple linear regressions, and predict values.

Case Study 03: Diabetes Classification (Logistic Regression)

Topics: Understand the structure of a dataset (PIMA Indians Diabetes dataset); implement multiple logistic regressions and classify; fit your model on the test and train data for prediction; evaluate your model using confusion matrix, and then visualize it

Case Study 04: Random Forest

Topics: Create a model that would help in classifying whether a patient ‘is normal,’ ‘is suspected to have a disease,’ or in actuality ‘has the disease’ using the ‘Cardiotocography’ dataset

Case Study 05: Principal Component Analysis (PCA)

Topics: Read the sample Iris dataset; use PCA to figure out the number of most important principal features, and then reduce the number of features using PCA; train and test the random forest classifier algorithm to check if reducing the number of dimensions is causing the model to perform poorly, and figure out the most optimal number that produces good quality results and predicts accurately

Case Study 06: K-means Clustering

Topics: Analyze data; extract useful columns from the dataset; visualize the data; find out the appropriate number of groups or clusters for the data to be segmented (using the elbow method); using k-means clustering, segment the data into k groups (k is found in the previous step); visualize a scatter plot of clusters, and a lot more

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Machine Learning Certification in Bangalore

Intellipaat’s course on ML, one of the most reputed Machine Learning courses in Bangalore is designed by industry professionals that will help you get the best jobs in top MNCs. As part of this Machine Learning with Python training, you will be engaged in real-time projects and assignments that have huge implications in real-world industry scenarios. This way, you can expedite your career effortlessly.

At the end of this Machine Learning training in Bangalore, you will find a quiz test that perfectly reflects the type of questions asked in the Machine Learning Certification exam, it will further help get a higher score.

Intellipaat Course Completion Certification will be issued after the project has been completed (after expert review) and upon scoring at least 60 percent on the quiz. You would be glad to know that Intellipaat certification is recognized by more than 100 top multinational companies, including Cisco, Ericsson, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered Bank, IBM, Infosys, Genpact, TCS, Hexaware and more.

Our Alumni works at top 3000+ companies

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Machine Learning Training Reviews in Bangalore

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Shreyash Limbhetwala

Technical Delivery Lead

I had completed this course a while back, and the job assistance they provided me was extremely supportive. The team offered mind-blowing support for upgrading my resume with the new skills that I had acquired during the course. They also conducted several mock interviews, which gave me confidence during my actual interview and helped me successfully land the job. Overall, it is the best online course for Machine Learning

Kavita Mehra

Hadoop Developer at TCS

This ML online course was up-to-date, and the instructor taught all the concepts in great detail. It was a very informative course with all the topics taught step by step. For a beginner like me, this course was amazing. It helped me a lot in becoming proficient in ML and Deep Learning concepts

Amitav Tripathy

Project Manager at Micro Focus

Overwhelming Machine Learning course with concepts taught in great detail. The 24-hour support provided was really helpful when I had to clear my doubts. Moreover, the resource material provided in this course was comprehensive and interesting, which made this course fun to learn

Bhanukumar Muppalla

Software Engineer at DXC Technology

I have done a couple of courses online from other online providers, but I was never quite satisfied. I recently took up this online ML training, and I am still going through it. But, unlike my previous experiences, this was very interactive and helped me grasp all concepts with a little effort.

Nandini Shankar

Senior Software Engineer at ACC Limited

I always had a keen interest in Artificial Intelligence and Machine Learning. Intellipaat Machine Learning classes are of high quality and trainers are the best in knowledge. I feel enrolling to the Intellipaat is the best decision made for my up skilling objective.

Satya

Sr. Manager at Cognizant Technology Solutions

I am an ML Engineer in a well-reputed organization. I started working here recently and I got this job opportunity only because of this best course on Machine Learning. I finished this course recently, and the job opportunities that came flooding in after I had received the certification was amazing

Adegboyega During

Keystone Bank Limited

Overall, the most delightful aspect of this Machine Learning online course was placement assistance. The team really did a great job in preparing me for a job interview by conducting a number of dummy interviews. I am extremely grateful to the team for helping me. They also help me to prepare my resume as per the job role I was seeking

Ramyasri Mandepudi

Recruiter at Goodwill Technologies

Concepts were taught from the basics, which was really helpful for me as I am not from a computer science background. Moreover, the course material was easily available and accessible even after I completed the course. This was convenient and helpful asI could refer to the concepts whenever I wanted

Vikrant Singh

Big Data Analytics

Excellent Machine Learning certification course with extremely interactive sessions. The course was very well delivered and structured. Even the complex concepts were taught with extreme ease with practical, real-life, and relatable examples. This helped a great deal in getting hold of the concepts and comprehending the same

Rich Baker

Director at SBD System

This Machine Learning with Python course was very comprehensive, well-planned, extremely organized, and elaborate. Besides, the assignments and projects that had to be solved after the course really helped in testing my skills and knowledge acquired through the course

Samar Jain

Business Analyst at McKinsey & Company

The training was amazing and the trainer did a great job of explaining it. He was extremely patient throughout the lectures and gave enough time and effort to explain each and every concept. I was extremely satisfied with this Machine Learning with Python course

Bharti karma

Analyst at Oracle India Pvt. Ltd

I had recently completed my AI and ML course with Intellipaat. All the concepts were clearly explained by the trainer. I was able to understand and grasp the concepts easily. Also, I could clear all my doubts related to the course on the given platform

Bharat Rathore

Expert in Data Analysis & Data Science

The ML training in Bangalore was top-notch and the course material was very good with lots of real-world examples of this awesome technology. Learning with Intellipaat was a great experience in Marathahalli! Fully recommend this, one of the prominent Machine Learning training institutes in Bangalore.

Raghavendra Narayan

Business Analyst at Tata Consultancy Services

They provide one of the best Machine Learning course in Bangalore in the market. 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 for conjuring the best Machine Learning training in Bangalore.

FAQ’s on Machine Learning Certification Course

Why should I learn online Machine Learning course in Bangalore from Intellipaat?

Intellipaat provides comprehensive Machine Learning training through hands-on projects and case studies. A few of the many reasons for choosing Intellipaat ML course includes:

  • You will learn various concepts such as Machine Learning using Python, classification techniques, linear and logistic regression, supervised and unsupervised learning, and more.
  • After successfully completing your Machine Learning online training, you will be awarded Intellipaat’s Machine Learning certification, which holds merit in 100+ MNCs across the world.
  • This course covers real-time ML projects and step-by-step tasks that are highly relevant in the corporate world. It also includes an extensive curriculum, created by industry experts.
  • Our Machine Learning certificate will allow you to compete for some of the best positions in the world’s leading MNCs for higher salaries.
  • We provide lifetime access to videos, course material, 24/7 learning support, and free upgrades to the latest version.

Intellipaat has been serving ML enthusiasts from every corner of the city. You can be living in any locality in Bengaluru, be it Marathalli, Koramangala, Btm Layout, Jayanagar, Sarjapur, Vijaynagar, Whitefield, HSR Layout, Indira Nagar, Electronic City or anywhere. You can have full-access to our Machine Learning online course sitting at home or office 24/7.

At Intellipaat, you can enroll in either 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, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.

Intellipaat is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.

You would be glad to know that you can contact Intellipaat support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.

Intellipaat offers self-paced training to those who want to learn at their own pace. This training also gives you the benefits of query resolution through email, live sessions with trainers, round-the-clock support, and access to the learning modules on LMS for a lifetime. Also, you get the latest version of the course material at no added cost.

Intellipaat’s self-paced training is 75 percent 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.

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 real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, 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. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

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 such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.

You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.

Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.

Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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Bangalore Address

Khykha Court, 1st Floor, No.5, I Cross, Madiwala, Hosur Main Road, Bangalore-560068, India+91-7022374614

Find Machine Learning Training in Other Regions

Hyderabad, Chennai, India, Pune, Mumbai, Delhi, Noida, Gurgaon, Jaipur and Chandigarh

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