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Data Science Training Course in Jersey

In this Data Science training course in Jersey 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 deploy market basket analysis in the retail sector. Get the best online data science training in Jersey from top data scientists

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Key Features

42 Hrs Instructor-led Training
28 Hrs Self-paced Videos
56 Hrs Project Work & Exercises
Flexible Schedule
24 x 7 Lifetime Support & Access
Certification and Job Assistance

Course Benefits

5/5 Student Satisfaction Rating
Students Transitioned for Higher Positions
Started a New Career After Completing Our Courses
Got Better Salary Hike and Promotion
Average Salary Per Year $200
$ Starting
$ Median
$ Experienced
And 1,000+ Global Companies

Data Science Course in Jersey Overview

Intellipaat Data Scientist training in Jersey is a comprehensive course that includes mastering the entire aspects of data analytics, data acquisition, deploying recommender systems, statistical methods, clustering methods and association rules through hands-on projects and case studies.

What will you learn in this Data Science training in Jersey?

Intellipaat is a premier online training institute which helps you master concepts like

  1. Data science tools and techniques
  2. Experimentation and evaluation methods
  3. Basics of Big Data and Hadoop integration with R
  4. Deploying recommender systems at scale
  5. Data manipulation and data mining
  6. Linear and non-linear regression models
  7. Classification technique for data analysis

Intellipaat’s online training course is exclusively designed by industry experts for

  • Big Data Specialists, Business Analysts and Business Intelligence Professionals
  • Statisticians looking to improve their Big Data statistics skills
  • Developers wanting to learn Machine Learning (ML) techniques
  • Information Architects looking to learn predictive analytics
  • Those looking to take up the roles of Data Science and Machine Learning Experts

There are no particular prerequisites for this training course. If you love mathematics, it is helpful.

Jersey City is rapidly growing, thanks to this city being located in a very prominent business area of the United States. Data Science job opportunities in city are extensive because of the heavy deployment of this domain in the enterprises located in this city.

According to Glassdoor, the average income of a Data Scientist in Jersey is US$122,801 per year.

  • Data Scientist is the best job in the 21st century – Harvard Business Review
  • The number of jobs for all data professionals in the United States will increase to 2.7 million as per a prediction by IBM– Forbes
  • Global Big Data market achieves US$122 billion in sales in 6 years – Frost & Sullivan

The demand for Data Scientists far exceeds the supply. This is a serious problem in a data-driven world that we are living in today. As a result, most organizations are willing to pay high salaries for professionals with appropriate Data Science skills.

Data scientist training online will help you become proficient in Data Science, R programming, Data Analysis, Big Data, and more. Thus, you can easily accelerate your career in this evolving domain and take it to the next level.

In this course, we have included real-world industry-based projects, which help you gain hands-on experience in the field and prepare you for challenging roles.

IndustryProject NameObjective
BFSIFraud Detection in Banking SystemDeploying Data Science to detect fraudulent activities and take remedial actions
EntertainmentMovie Recommendation EngineBuilding a movie recommendation engine, based on user interests
E-commerceMaking Sense of Customer Buying PatternsDeploying target selling to customers

Top companies that hire Data Scientists are:

  • Fidelity Investments
  • Accenture
  • Aon
  • Oath
  • MSD
  • Intel
  • Amazon
  • Google
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Fees

Self Paced Training

  • 28 Hrs e-learning videos
  • Lifetime Free Upgrade
  • 24 x 7 Lifetime Support & Access
$264

Online Classroom preferred

  • Everything in self-paced, plus
  • 42 Hrs of Instructor-led Training
  • 1:1 Doubt Resolution Sessions
  • Attend as many batches for Lifetime
  • Flexible Schedule
  • 27 Sep
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 29 Sep
  • TUE - FRI
  • 07:00 AM TO 09:00 AM IST (GMT +5:30)
  • 03 Oct
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
  • 11 Oct
  • SAT - SUN
  • 08:00 PM TO 11:00 PM IST (GMT +5:30)
$ 499 $399 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise-grade Learning Management System (LMS)
  • 24x7 Support
  • Strong Reporting

Data Science Course Content

Module 01 - Introduction to Data Science with R Preview

1.1 What is Data Science?
1.2 Significance of Data Science in today’s data-driven world, applications of Data Science, lifecycle of Data Science, and its components
1.3 Introduction to Big Data Hadoop, Machine Learning, and Deep Learning
1.4 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

Module 02 - Data Exploration

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

Self-paced Course Content

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

Case Study 01: Market Basket Analysis (MBA)

1.1 This case study is associated with the modeling technique of Market Basket Analysis, where you will learn about loading data, plotting items, and running algorithms.
1.2 It includes finding out the items that go hand in hand and can be clubbed together.
1.3 This is used for various real-world scenarios like a supermarket shopping cart and so on.

Case Study 02: Logistic Regression

2.1 In this case study, you will get a detailed understanding of the advertisement spends of a company that will help drive more sales.
2.2 You will deploy logistic regression to forecast future trends.
2.3 You will detect patterns and uncover insight using the power of R programming.
2.4 Due to this, the future advertisement spends can be decided and optimized for higher revenues.

Case Study 03: Multiple Regression

3.1 You will understand how to compare the miles per gallon (MPG) of a car based on various parameters.
3.2 You will deploy multiple regression and note down the MPG for car make, model, speed, load conditions, etc.
3.3 The case study includes model building, model diagnostic, and checking the ROC curve, among other things.

Case Study 04: Receiver Operating Characteristic (ROC)

4.1 In this case study, you will work with various datasets in R.
4.2 You will deploy data exploration methodologies.
4.3 You will also build scalable models.
4.4 Besides, you will predict the outcome with highest precision, diagnose the model that you have created with real-world data, and check the ROC curve.

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42
Hours of Instructor-led Training
28
Hours of Self-paced Videos
7
Guided Projects to Practice
24/7
Lifetime Technical Support

Free Career Counselling

Data Science Projects

What projects will I be working on in this Data Science certification course?

Project 01: Market Basket Analysis

Domain: Inventory Management

Problem Statement: As a new manager in the company, you are assigned the task of increasing cross selling

Topics: Association rule mining, data extraction, and data manipulation

Highlights:

  • Performing association rule mining
  • Understanding where to implement the apriori algorithm
  • Setting association rules with respect to confidence

Project 02: Credit Card Fraud Detection

Domain: Banking

Problem Statement: Analyze the probability of being involved in a fraudulent operation

Topics: Algorithms, V17 predictor, data visualization, and R

Highlights:

  • Working with the credit card dataset
  • Performing data analysis on various labels in the data
  • Making use of V17 as predictor and using V14 for analysis
  • Plotting score performance with respect to variables

Project 03: Data Cleaning Using the Census Dataset

Domain: Government

Problem Statement: Perform data cleansing on the raw dataset

Topics: Data analysis, data preprocessing, cleaning ops, data visualization, and R

Highlights:

  • Working with the census dataset
  • Changing a label to perform analysis
  • Creation of functions to eliminate values that are not required
  • Verifying the completion of data cleansing

Project 04: Loan Approval Prediction

Domain: Banking

Problem Statement: Predict the approval rate of a loan by using multiple labels

Topics: Data analysis, data preprocessing, cleaning ops, data visualization, and R

Highlights:

  • Performing data preprocessing
  • Building a model and applying PCA
  • Building a Naïve Bayes model on the training dataset
  • Prediction of values after performing analysis

Project 05: Designing a Book Recommendation System

Domain: Ecommerce

Problem Statement: Create a model, which can recommend books, based on user interest

Topics: Data cleaning, data visualization, and user-based collaborative filtering

Highlights:

  • Finding the most popular books using various techniques
  • Creating a book recommender model using user-based collaborative filtering

Project 06: Netflix Recommendation System

Domain: Ecommerce

Problem Statement: Simulate the Netflix recommendation system

Topics: Data cleaning, data visualization, distribution, and Recommender Lab

Highlights:

  • Working with raw data
  • Using the Recommender Lab library in R
  • Making use of real data from Netflix

Project 07: Creating a Pokemon Game Using Machine Learning

Domain: Gaming

Problem Statement: Create a game engine for Pokemon using Machine Learning

Topics: Decision trees, regression, data cleaning, and data visualization

Highlights:

  • Predicting which Pokemon will win based on ‘Attack vs Defense’
  • Finding whether a Pokemon is legendary using decision trees
  • Understanding the dynamics of decision-making in Machine Learning

Case Study 01: Introduction to R Programming

Problem Statement: Working with various operators in R

Topics: Arithmetic operators, relational operators, and logical operators

Highlights:

  • Working with arithmetic operators
  • Working with relational operators
  • Working with logical operators

Case Study 02: Solving Customer Churn Using Data Exploration

Problem Statement: Understanding what to do to reduce customer churn using data exploration

Topics: Data Exploration

Highlights:

  • Extracting individual columns
  • Creating and applying filters to manipulate data
  • Using loops for redundant operations

Case Study 03: Creating Data Structures in R

Problem Statement: Implementing various data structures in R for various scenarios

Topics: Vectors, lists, matrices, and arrays

Highlights:

  • Creating and implementing vectors
  • Understanding lists
  • Using arrays to store matrices
  • Creating and implementing matrices

Case Study 04: Implementing SVD in R

Problem Statement: Understanding the use of single value decomposition in R by making use of the MovieLense dataset

Topics: 5-fold cross validation and realRatingMatrix

Highlights:

  • Creating custom recommended movie sets for each user
  • Creating a user-based collaborative filtering model
  • Creating realRatingMatrix for movie recommendation

Case Study 05: Time Series Analysis

Problem Statement: Performing TSA and understanding the concepts of ARIMA for a given scenario

Topics: Time series analysis, R language, data visualization, and the ARIMA model

Highlights:

  • Understanding how to fit an ARIMA model
  • Plotting PACF charts and finding optimal parameters
  • Building the ARIMA model
  • Prediction of values after performing analysis
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Data Science Certification in Jersey

The entire Data Science course content is designed by industry professionals for you to get the best jobs in top MNCs. As part of Data Science online courses, 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 Data Science online training program, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams.They will help you score better.

Intellipaat’s course completion certificate will be awarded to you when you complete the project work and score at least 60 percent marks in the quiz. This certification is well recognized in the top 80+ MNCs,such as Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Standard Chartered, TCS, Genpact, etc.

Data Science Training Review

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Mr Yoga

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John Chioles

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Ritesh

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Dileep & Ajay

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Sagar

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Ashok

Swetha Pandit

Big Data Developer at Accenture

Intellipaat’s Data scientist certification training in Jersey online are well structured and taught by recognized professionals. They help one learn it fast. I have found their videos to be of excellent quality. Thanks a lot!

Giri Karnal

Professional

I had taken the Data Science master’s program, which is a combo of SAS, R, and Apache Mahout. Since there are so many technologies involved in training courses, 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.

Nitesh Kumar Dash

Professional

Intellipaat’s training videos really made me excited about studying Data Science. They were so elaborate and so professionally created. I could learn it from the comfort of my home, thanks to those learner-friendly videos. I am grateful to Intellipaat!

Vikrant Singh

Big Data Analytics

It was a wonderful experience learning online from Intellipaat. The trainers were hands-on and provided real-time scenarios. According to me, for learning cutting-edge technologies, Intellipaat is the right place.

Bhanukumar Muppalla

Software Engineer at DXC Technology

This 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.

Bharat Rathore

Expert in Data Analysis & Data Science

I really appreciate the quality of the material and the content of this certification course!! Thanks to all Intellipaat team!

Thejaswar Reddy

Programmer Analyst

I had enrolled for Data science course in Intellipaat. Intellipaat is a good place for learning. Material provided by the institute is nice, course material is good but can be improved even more. I had opted for weekend classes as it was more convenient for me. The trainer was good and taught us the subject well. Support team helped me to solve technical issue whenever i faced.

Sudipto

PS Consultant at Genesys

Intellipaat’s Data Scientist training in Jersey is outstanding. The trainer is an experienced Data Scientist who has a good hold on the subject. Now, I’m an expert in Data Science, and I am already placed in a reputed firm.

Varsha Tyagi

Cloud Architect at Huawei Technologies

I was searching for Data Science courses online, 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. Really appreciable!

Shreyash Limbhetwala

Technical Delivery Lead

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.

Kevin K Wada

Oracle Developer at Free Agent

Thank you very much for your top-class service. A special mention should be made for your patience in listening to my queries and giving me a solution, which was exactly what I was looking for. I am giving you a 10 on 10!

Ramyasri Mandepudi

Recruiter at Goodwill Technologies

My issue was 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.

Prasil das

SEO Specialist at Jain

Awesome response to queries! Thanking you for resolving all my issues and helping me learn tough concepts through highly insightful videos.

Sulekha Roy

Sr. Data scientist at Hewlett Packard Enterprise

I think this online 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.

Kavita Mehra

Hadoop Developer at TCS

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.

Data Science Training in Jersey FAQ

Why should I learn Data Science from Intellipaat?

Intellipaat offers exclusive Data Science course in Jersey for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by SMEs
  • Extensive LMS, allowing you to view recorded sessions within 3 hours
  • Real-time exercises, assignments, and projects
  • 24/7 learning support
  • Large community of like-minded learners
  • Industry-recognized Intellipaat badge
  • Personalized job support

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.

This online training is curated by top Data Scientists from India and the United States. These SMEs have designed the course in such a manner that even if you are from a non-technical background and have almost zero knowledge of this domain, you can still learn and adapt all concepts easily. Also, we provide practical experience through real-time projects that allow even freshers to easily grasp the concepts.

Intellipaat does not directly forward resumes to any companies or recruiters. However, we do have a placement team that will conduct a number of mock interviews and will assist you in updating your resume to prepare you for job interviews. The team thus helps you land a lucrative job in the domain.

Intellipaat provides various group offers and discounts for its online training as per the size and type of the particular group. If you wish to avail the discount, you need to get in touch with our course advisors who will explain to you all the details regarding it.

In the career mentoring session at Intellipaat, our Data Science experts offer solutions to all your queries that are based on career opportunities and the growth available in this domain.

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 online 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.

In this online training, in collaboration with IBM, you can expect several benefits, including the following:

  • Free course upgrade throughout a lifetime
  • Anytime online assistance
  • Industry-recognized course completion certification from Intellipaat and IBM
  • Lifelong access to the entire courseware

If you wish to enroll in our Data Scientist training in Jersey, then you need to first make a choice between online instructor-led training and self-paced training. Once you do that, you can make the payment using any major credit card, debit card, or EMI options.

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.

Jersey City is growing at a rapid rate with diverse types of industries such as banking, finance, logistics, transportation and high technology, all calling it their home. Data Science market is growing at a robust rate in the City, and professionals can benefit from this growing trend by getting trained and certified.

Intellipaat online course comprises all the topics that are required and significant to learn so that you can master this technology. Intellipaat’s Data Science course in Jersey comprises both basic and advanced-level concepts involved in this technology so that you can learn them and master the skills to pursue a career in this domain. Moreover, the trainers of this course are experts in the domain who spend time and effort to teach you all the concepts in detail.

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 $264, while our online instructor-led training for the same costs $399.

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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