Courses
×
Courses
×
Intellipaat’s Data Science course in Mumbai helps you master Data Analytics, Business Analytics, data modeling, Machine Learning algorithms, k-means clustering, Naïve Bayes, etc. This training will help you learn R statistical computing, building recommendation engine for e-commerce, recommending movies, and deploying market basket analysis in the retail sector. Get the best program in Data Science training at Mumbai from top Data Scientists.
Intellipaat offers the best Data Scientist training in Mumbai that is created by industry professionals with extensive experience and in-depth knowledge. This course will equip you with the right skills in data analysis, clustering, data mining, cleansing, Machine Learning, data transformation, visualization, and more.
Data Science can help you upgrade your career if you have the right Course in this domain. Today, almost all industry verticals, regardless of their customer orientation, are actively hiring Data Scientists making it very worthwhile to get certified.
Intellipaat is a premier online training institute which helps you master concepts like
Intellipaat’s Data Science in Mumbai course is exclusively designed by industry experts for:
There are no particular prerequisites for this course. If you love mathematics, it is helpful.
This city is India’s business and financial capital, and as such, there is a huge demand for qualified professionals here. Various lucrative jobs are heating up in the finance, IT, banking, insurance, advertising, marketing, and software domains.
According to Glassdoor, the average income of a Data Scientist is ₹1,049k per year.
This Data Science institute in Mumbai has included real-world industry-based projects in this course, which will help you gain hands-on experience in the field and prepare you for challenging roles.
| Industry | Project Name | Objective |
| BFSI | Fraud Detection in Banking System | Deploying Data Science to detect fraudulent activities and take remedial actions |
| Entertainment | Movie Recommendation Engine | Building a movie recommendation engine, based on user interests |
| E-commerce | Making Sense of Customer Buying Patterns | Deploying target selling to customers |
Talk to Us
1.1 What is Data Science?
1.2 Significance of Data Science in today’s data-driven world, its applications of, , lifecycle, and its components
1.3 Introduction to R programming and RStudio
Hands-on Exercise:
1. Installation of RStudio
2. Implementing simple mathematical operations and logic using R operators, loops, if statements, and switch cases
2.1 Introduction to data exploration
2.2 Importing and exporting data to/from external sources
2.3 What are data exploratory analysis and data importing?
2.4 DataFrames, working with them, accessing individual elements, vectors, factors, operators, in-built functions, conditional and looping statements, user-defined functions, and data types
Hands-on Exercise:
1. Accessing individual elements of customer churn data
2. Modifying and extracting results from the dataset using user-defined functions in R
3.1 Need for data manipulation
3.2 Introduction to the dplyr package
3.3 Selecting one or more columns with select(), filtering records on the basis of a condition with filter(), adding new columns with mutate(), sampling, and counting
3.4 Combining different functions with the pipe operator and implementing SQL-like operations with sqldf
Hands-on Exercise:
1. Implementing dplyr
2. Performing various operations for manipulating data and storing it
4.1 Introduction to visualization
4.2 Different types of graphs, the grammar of graphics, the ggplot2 package, categorical distribution with geom_bar(), numerical distribution with geom_hist(), building frequency polygons with geom_freqpoly(), and making a scatterplot with geom_pont()
4.3 Multivariate analysis with geom_boxplot
4.4 Univariate analysis with a barplot, a histogram and a density plot, and multivariate distribution
4.5 Creating barplots for categorical variables using geom_bar(), and adding themes with the theme() layer
4.6 Visualization with plotly, frequency plots with geom_freqpoly(), multivariate distribution with scatter plots and smooth lines, continuous distribution vs categorical distribution with box-plots, and sub grouping plots
4.7 Working with co-ordinates and themes to make graphs more presentable, understanding plotly and various plots, and visualization with ggvis
4.8 Geographic visualization with ggmap() and building web applications with shinyR
Hands-on Exercise:
1. Creating data visualization to understand the customer churn ratio using ggplot2 charts
2. Using plotly for importing and analyzing data
3. Visualizing tenure, monthly charges, total charges, and other individual columns using a scatter plot
5.1 Why do we need statistics?
5.2 Categories of statistics, statistical terminology, types of data, measures of central tendency, and measures of spread
5.3 Correlation and covariance, standardization and normalization, probability and the types, hypothesis testing, chi-square testing, ANOVA, normal distribution, and binary distribution
Hands-on Exercise:
1. Building a statistical analysis model that uses quantification, representations, and experimental data
2. Reviewing, analyzing, and drawing conclusions from the data
6.1 Introduction to Machine Learning
6.2 Introduction to linear regression, predictive modeling, simple linear regression vs multiple linear regression, concepts, formulas, assumptions, and residuals in Linear Regression, and building a simple linear model
6.3 Predicting results and finding the p-value and an introduction to logistic regression
6.4 Comparing linear regression with logistics regression and bivariate logistic regression with multivariate logistic regression
6.5 Confusion matrix the accuracy of a model, understanding the fit of the model, threshold evaluation with ROCR, and using qqnorm() and qqline()
6.6 Understanding the summary results with null hypothesis, F-statistic, and
building linear models with multiple independent variables
Hands-on Exercise:
1. Modeling the relationship within data using linear predictor functions
2. Implementing linear and logistics regression in R by building a model with ‘tenure’ as the dependent variable
7.1 Introduction to logistic regression
7.2 Logistic regression concepts, linear vs logistic regression, and math behind logistic regression
7.3 Detailed formulas, logit function and odds, bivariate logistic regression, and Poisson regression
7.4 Building a simple binomial model and predicting the result, making a confusion matrix for evaluating the accuracy, true positive rate, false positive rate, and threshold evaluation with ROCR
7.5 Finding out the right threshold by building the ROC plot, cross validation, multivariate logistic regression, and building logistic models with multiple independent variables
7.6 Real-life applications of logistic regression
Hands-on Exercise:
1. Implementing predictive analytics by describing data
2. Explaining the relationship between one dependent binary variable and one or more binary variables
3. Using glm() to build a model, with ‘Churn’ as the dependent variable
8.1 What is classification? Different classification techniques
8.2 Introduction to decision trees
8.3 Algorithm for decision tree induction and building a decision tree in R
8.4 Confusion matrix and regression trees vs classification trees
8.5 Introduction to bagging
8.6 Random forest and implementing it in R
8.7 What is Naive Bayes? Computing probabilities
8.8 Understanding the concepts of Impurity function, Entropy, Gini index, and Information gain for the right split of node
8.9 Overfitting, pruning, pre-pruning, post-pruning, and cost-complexity pruning, pruning a decision tree and predicting values, finding out the right number of trees, and evaluating performance metrics
Hands-on Exercise:
1. Implementing random forest for both regression and classification problems
2. Building a tree, pruning it using ‘churn’ as the dependent variable, and building a random forest with the right number of trees
3. Using ROCR for performance metrics
9.1 What is Clustering? Its use cases
9.2 what is k-means clustering? What is canopy clustering?
9.3 What is hierarchical clustering?
9.4 Introduction to unsupervised learning
9.5 Feature extraction, clustering algorithms, and the k-means clustering algorithm
9.6 Theoretical aspects of k-means, k-means process flow, k-means in R, implementing k-means, and finding out the right number of clusters using a scree plot
9.7 Dendograms, understanding hierarchical clustering, and implementing it in R
9.8 Explanation of Principal Component Analysis (PCA) in detail and implementing PCA in R
Hands-on Exercise:
1. Deploying unsupervised learning with R to achieve clustering and dimensionality reduction
2. K-means clustering for visualizing and interpreting results for the customer churn data
10.1 Introduction to association rule mining and MBA
10.2 Measures of association rule mining: Support, confidence, lift, and apriori algorithm, and implementing them in R
10.3 Introduction to recommendation engines
10.4 User-based collaborative filtering and item-based collaborative filtering, and implementing a recommendation engine in R
10.5 Recommendation engine use cases
Hands-on Exercise:
1. Deploying association analysis as a rule-based Machine Learning method
2. Identifying strong rules discovered in databases with measures based on interesting discoveries
11.1 Introducing Artificial Intelligence and Deep Learning
11.2 What is an artificial neural network? TensorFlow: The computational framework for building AI models
11.3 Fundamentals of building ANN using TensorFlow and working with TensorFlow in R
12.1 What is a time series? The techniques, applications, and components of time series
12.2 Moving average, smoothing techniques, and exponential smoothing
12.3 Univariate time series models and multivariate time series analysis
12.4 ARIMA model
12.5 Time series in R, sentiment analysis in R (Twitter sentiment analysis), and text analysis
Hands-on Exercise:
1. Analyzing time series data
2. Analyzing the sequence of measurements that follow a non-random order to identify the nature of phenomenon and forecast the future values in the series
13.1 Introduction to Support Vector Machine (SVM)
13.2 Data classification using SVM
13.3 SVM algorithms using separable and inseparable cases
13.4 Linear SVM for identifying margin hyperplane
14.1 What is the Bayes theorem?
14.2 What is Naïve Bayes Classifier?
14.3 Classification Workflow
14.4 How Naive Bayes classifier works and classifier building in Scikit-Learn
14.5 Building a probabilistic classification model using Naïve Bayes and the zero probability problem
15.1 Introduction to the concepts of text mining
15.2 Text mining use cases and understanding and manipulating the text with ‘tm’ and ‘stringR’
15.3 Text mining algorithms and the quantification of the text
15.4 TF-IDF and after TF-IDF
Market Basket Analysis
This is an inventory management project where you will find the trends in the data that will help the company to increase sales. In thisRead More..
Credit Card Fraud Detection
The project consists of data analysis for various parameters of banking dataset. You will be using a V7 predictor, V4 predictor for analysis, and dataRead More..
Loan Approval Prediction
In this project, you will use the banking dataset for data analysis, data cleaning, data preprocessing, and data visualization. You will implement algorithms such asRead More..
Netflix Recommendation System
Implement exploratory data analysis, data manipulation, and visualization to understand and find the trends in the Netflix dataset. You will use various Machine Learning algorithmsRead More..
Case Study 1: Introduction to R Programming
In this project, you need to work with several operators involved in R programming including relational operators, arithmetic operators, and logical operators for various organizationalRead More..
Case Study 2: Solving Customer Churn Using Data Exploration
Use data exploration in order to understand what needs to be done to make reductions in customer churn. In this project, you will be requiredRead More..
Case Study 3: Creating Data Structures in R
Implement numerous data structures for numerous possible scenarios. This project requires you to create and use vectors. Further, you need to build and use metrics,Read More..
Case Study 4: Implementing SVD in R
Utilize the dataset of MovieLens to analyze and understand single value decomposition and its use in R programming. Further, in this project, you must buildRead More..
Case Study 5: Time Series Analysis
This project required you to perform TSA and understand ARIMA and its concepts with respect to a given scenario. Here, you will use the RRead More..
The entire Data Science course content is designed by industry professionals for you to get the best jobs in top MNCs. As part of this Data Science online program, you will be working on various projects and assignments that have immense implications in real-world scenarios. They will help you fast-track your career effortlessly.
At the end of this program, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams. They will help you score better.
Excellent course, I found Intellipaat's training team to be talented in their respective domain. My training was very good as it helped me in upgrading my skills, which proved to be a turning point in my career. Intellipaat's mentor was well-experienced and his teaching method was really great. This online course helped me to get deep understanding of the technology. Moreover, the excercise and projectsRead More..
I want to talk about the rich LMS that Intellipaat’s Data Science program offered. The extensive set of PPTs, PDFs, and other related material were of the highest quality, and due to this, my learning with Intellipaat was excellent. I could clear the Cloudera Data Scientist certification exam in the first attempt.
I signed up for Intellipaat's Data Science course when I learned that it is a great place for learning new technologies. The training material offered by them was extremely useful. I chose to opt for the weekend classes as per my convenience. The trainer of this course was really good and helped me learn the subject well. Besides, the online support team helped me resolveRead More..
I had taken up the Data Science master’s program, which is a combo of SAS, R, and Apache Mahout. Since there are so many technologies involved in this course, getting our query resolved at the right time becomes the most important aspect. But with Intellipaat, there was no such problem as all my queries were resolved in less than 24 hours.
Bharat Rathore
I really appreciate the quality of the material and the content of this Data Science certification course!! Thanks to all Intellipaat team!
Kavita Mehra
The classes were highly interactive and also practical oriented. The office staff was cordial. Every teaching session was recorded each day and was put online. The trainer was very patient and giving hints to solve all the questions posed to him.
Sulekha Roy
I think this online Data Science course is a good way to start learning Data Science and make a career in it. Instructors are reasonably good. Also, projects were interesting and relevant to the current industry trends.
My issues were resolved, thanks to the deep domain expertise of the trainer. I am greatly indebted to Intellipaat for assigning such knowledgeable and experienced trainers for this certification course. It really makes a difference to the learner.
Data Science training online includes a lot of constituent components, and Intellipaat’s course provided the most comprehensive and in-depth learning experience. I really liked the real-world projects which helped me take on a Data Science role in a reputed company much easier.
I had taken up the Data Science master’s program, which is a combo of SAS, R, and Apache Mahout. Since there are so many technologies involved in this course, getting our query resolved at the right time becomes the most important aspect. But with Intellipaat, there was no such problem as all my queries were resolved in less than 24 hours.
I want to talk about the rich LMS that Intellipaat’s Data Science program offered. The extensive set of PPTs, PDFs, and other related material were of the highest quality, and due to this, my learning with Intellipaat was excellent. I could clear the Cloudera Data Scientist certification exam in the first attempt.
Swetha Pandit
Intellipaat’s Data Scientist certification in Mumbai online is well structured and taught by SMEs. They helped me learn Data Science fast. I have found their videos to be of excellent quality. Thanks a lot!
I was searching for the best Data Science classes in Mumbai, and I landed on Intellipaat’s. It was really good in terms of content. The sample video provided was also awesome, which impressed me a lot while deciding to take up the course. Moreover, the trainer’s command over the technology was great. The support team was really good as well. Really appreciable!
I signed up for Intellipaat's Data science course when i learned that it is a great place for learning new technologies. The training material offered by them is extremely useful. I chose to opt for the weekend classes as per my convenience . The trainer of this course was really good and helped me learn the subject well. Besides, the online support team helped meRead More..
Great course! I had a really good experience with this platform; they trained me well. I completed my training with this institute where they provided extremely good training and good support too. Further, the course instructors were really well-educated who explained all the topics with great enthusiasm.
Genuine platform for learning. I finished my course recently from Intellipaat. The trainers were excellent in teaching. Further, the course was well-structured and the lectures are really flexible. I am currently working and I still get the time to complete the course within the given time and it is mainly possible because of the 24*7 support systemRead More.. and the clarity of their teaching. Besides,Read More..
Great training program. It was an amazing experience learning from Intellipaat. During this COVID-19, it was extremely fruitful to learn and spend ample amount of time as a part of this institute. Intellipaat has also provided great support during the course. Besides, the instructor was very supportive in the course, guidance was also givenRead More.. to complete assignment and project which was very helpful.
Intellipaat offers exclusive Data Scientist course in Mumbai for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:
Intellipaat offers one of the top Data Scientist courses in Mumbai that will help you to become a Data Science expert. The courses like R Certification, Artificial Intelligence, Machine Learning, Data Analytics, Python for Data Science, Python, Business Analytics and others are hands-on practical-based training program.
To learn Data Science for free, you need to take a look at the blogs and youtube videos published by Intellipaat. Read the top blogs on its Interview Questions, Tutorial and everything about Data Science.
In the career mentoring session at Intellipaat, our experts offer solutions to all your queries that are based on career opportunities and the growth available in this domain.
In this online training, in collaboration with IBM, you can expect several benefits, including the following:
For Intellipaat courses, geographical boundaries does not apply. It does not matter in whichever area of Mumbai you are in, be it Worli, Bandra, Andheri East, Powai, Navi Mumbai, Thane, Panvel, Nariman Point, Airoli, Parel, or anywhere. You can access our online course sitting at home or office.
Intellipaat selects subject matter experts from top MNCs, who have at least 8 to 12 years of experience in the domain, as instructors. They are qualified Data Science instructors and are selected after going through our rigorous selection process and proving their capabilities.
Intellipaat’s teaching assistants are SMEs whose main aim is to make you a certified professional in the respective domain. The trainers conduct interactive video lectures to teach the latest technologies and enrich your experience with various industry-based projects. The teaching assistance provided by Intellipaat is only available during regular hours.
The market for Data Science in Mumbai is growing rapidly. Since the city is home to some of the biggest organizations from around the world that exclusively employ Data Scientists. There is a huge market for professionals with skills in statistical analysis, Machine Learning and advanced analytics, among other things.
Since it involves various aspects of advanced technologies, such as Machine Learning, Deep Learning, and Artificial Intelligence, among others, it is comparatively difficult to learn. However, Intellipaat’s training is offered by experts in this domain who have a lot of experience in the field. They make all concepts easier to understand as they explain each concept with the help of several real-life examples.
Yes Fresher’s can also take up this course and there is no pre-requisite for taking up this course.
Intellipaat is one of the most affordable e-learning providers today. It offers both online training and self-paced training, and you can avail them at their respective costs. Our self-paced training costs about ₹15,048, while our online instructor-led training for the same costs ₹22,743.
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 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.
Talk to us
Kolkata, Delhi, Chennai, Noida, Pune, Bangalore, Hyderabad, India, Jaipur, Gurgaon, Indore, Ahmedabad, Coimbatore, Kochi, Chandigarh, Bhubaneswar, Trichy, Nagpur, Vizag, Trivandrum, Vijayawada, Thane, Jamshedpur, Kerala, Lucknow, Tamil Nadu, Vadodara, Ludhiana and Surat
Master’s in Artificial Intelligence
Big Data and Data Science Master’s Course
Big Data Architect Master’s Course
Master’s in Data Science Program Online
