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Data Science Course in Raleigh

92,113 Ratings

Data Science program in Raleigh in association with iHUB, IIT Roorkee empowers you with skills such as GIT, AI, Deep Learning using TensorFlow, and others through the use of real-world projects. Learn from IIT Roorkee faculty and industry professionals, and earn a certification from IIT Roorkee.

Ranked #1 Data Science Course by India TV

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Data Science Training in Raleigh Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Roorkee Faculty and Industry Practitioners
1:1 with Industry Mentors and 24*7 Support
Resume Preparation and LinkedIn Profile Review
Campus Immersion at IIT Roorkee
No-cost EMI Option
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Data Science Course Overview

Why should you take up the Data Scientist course in Raleigh?

  • As per Glassdoor, the average income of Data Scientists in India is about ₹10,04,082 per annum
  • LinkedIn has over 5,000 Data Science job opportunities in India
  • Data Scientist is the best job of the 21st century – Harvard Business Review, 2023
  • The global Big Data market to reach US$128.5 billion in revenue in 6 years – Frost & Sullivan
  • The number of jobs for all the US data professionals will increase to 2.85 million per year – IBM

Today, almost all industry verticals, regardless of their customer orientation, are actively hiring Data Scientists, which makes it truly worthwhile to get certified.

Intellipaat is a premier online coaching institute that offers the best Data Science courses in Raleigh, which help you master concepts such as

  1. Techniques of evaluation, experimentation, and project deployment
  2. Machine Learning algorithms
  3. Data Science at scale with PySpark, AI with TensorFlow
  4. Data analysis, project life cycle, and Data Science in the real world
  5. Analysis segmentation using clustering and the technique of prediction
  6. Git, Storytelling
  7. Deploying Machine Learning models on Clouds (MLOps)
  8. Data visualization with Tableau
  9. Natural Language Processing and its applications
  10. Python with Data Science
  11. Data Science projects, analytics, and recommender systems
  12. Microsoft Excel for data analysis and data transformation

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

  • Big Data Statisticians
  • Information Architects and Predictive Analytics Experts
  • BI Professionals and Analysts
  • Freshers or Professionals looking for a Data Science career
  • Big Data Experts
  • Machine Learning Professionals

There are no special prerequisites for this Data Scientist course in Raleigh. If you like mathematics, then it will help you.

According to Glassdoor, the average income of a Data Scientist in Raleigh is ₹10Lakhs per year.

On average, a Data Scientist earns around ₹1,000,000/year, which is almost 20 percent more than the national average. One of the top five skills that pay the most in the domain includes

  • Data Analysis – ₹983,000/year
  • Python – ₹980,000/year
  • Statistical Analysis – ₹1,100,000/year
  • R – ₹985,000/year
  • Machine Learning – ₹1,050,000/year

Some of the top employers hiring professionals in this domain are Mu Sigma, Amazon, EY, IBM, Accenture, Flipkart, Robert Bosch, etc. Also, the city, often called the Silicon Valley of India, is home to thousands of startups that are actively looking for certified professionals.

Top companies that hire Data Scientists are:

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

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.

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
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Talk To Us

We are happy to help you 24/7

With data collection, ‘the sooner, the better’ is the best answer. - The CEO of Yahoo
Everything is going to be connected with data and mediated by software - The CEO of Microsoft
The world is now awash in data, and we can see consumers more cleanly - The Co-founder of PayPal

Career Transition

55% Average Salary Hike

$1,20,000 The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Science Mentors

Who can apply for the Data Scientist course?

  • Information Architects and Statisticians
  • Developers looking to master Machine Learning and Predictive Analytics
  • Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
  • Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
  • Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
Who can apply

What roles does a Data Scientist play?

Data Scientist

Design and implement scalable codes alongside effectively developing high-quality applications.

Analytics and Insights Analyst

Develop solutions for fixing quality issues in the data upon investigating the reported errors in the data.

AI & ML Engineer

Use Lambda functions and API Gateway to integrate machine learning models into web apps and deploy models in SageMaker.

Data Engineer & Data Analyst

Perform data cleansing, and data transformation, analyze the outcomes, and present the insights in reports and dashboards.

Junior Data Scientist

Analyze the operating behavior using advanced statistical techniques and tools. Also, create algorithms with prescriptive and descriptive methods.

Applied Scientist

Derive intelligence for business products through designing and developing machine learning models.

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Skills Covered

Python

Data Science

Data Analysis

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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Data Science Course Fees in Raleigh

Online Classroom Preferred

  • Live Classes from iHUB IIT Roorkee Faculty & Industry Experts
  • Certification from iHUB IIT Roorkee
  • Career Services (Mock Interviews, Resume Preparation)
  • Placement Assistance upon clearing PRT
  • Dedicated Learning Manager
31 Mar

SAT - SUN

10:00 AM TO 01:00 PM IST (GMT +5:30)

06 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

13 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

20 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,229 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Data Scientist Training Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

Preview

Python 

  • Introduction to Python and IDEs – The basics of the Python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc. 
  • Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
  • Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice – The culmination of all the above concepts with real-world problem statements for better understanding. 

Linux

  • Introduction to Linux  – Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS. 
  • Linux Basics – File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux. 
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Module 2 – Data Wrangling with SQL

Preview

SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, Variables 

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table. 
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc. 
  • Clustered indexes, common table expressions.

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Extract Transform Load

  • Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, Matrices.

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib.
  • Regression plots, categorical plots, area plots, etc, with Python seaborn.
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, central limit theorem. 

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning.
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  • How to train the model in a regression problem.
  • How to evaluate the model for a regression problem.
  • How to optimize the efficiency of the regression model.

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables.
  • How to train the model in a classification problem.
  • How to evaluate the model for a classification problem.
  • How to optimize the efficiency of the classification model.

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  • How to train the model in a clustering problem.
  • How to evaluate the model for a clustering problem.
  • How to optimize the efficiency of the clustering model.
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  • Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree – Creating decision tree models on classification problems in a tree like format with optimal solutions.
  • Random Forest – Creating random forest models for classification problems in a supervised learning approach.
  • Support Vector Machine – SVM or support vector machines for regression and classification problems.
  • Gradient Descent – Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function.
  • K-Nearest Neighbors – A simple algorithm that can be used for classification problems.
  • Time Series Forecasting – Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.
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  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  • Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data.
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data.

Performance Metrics

  • Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix – To evaluate the true positive/negative, and false positive/negative outcomes in the model.
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning 

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks 
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted boltzmann machine 
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The Data Science capstone project focuses on establishing a strong hold of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals: 

  • Extracting, loading and transforming data into usable format to gather insights. 
  • Data manipulation and handling to pre-process the data.
  • Feature engineering and scaling the data for various problem statements. 
  • Model selection and model building on various classification, regression problems using supervised/unsupervised machine learning algorithms.
  • Assessment and monitoring of the model created using the machine learning models.
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  • Recommendation Engine – The case study will guide you through various processes and techniques in machine learning to build a recommendation engine that can be used for movie recommendations, restaurant recommendations, book recommendations, etc.
  • Rating Predictions – This text classification and sentiment analysis case study will guide you towards working with text data and building efficient machine learning models that can predict ratings, sentiments, etc.
  • Census – Using predictive modeling techniques on the census data, you will be able to create actionable insights for a given population and create machine learning models that will predict or classify various features like total population, user income, etc.
  • Housing – This real estate case study will guide you towards real world problems, where a culmination of multiple features will guide you towards creating a predictive model to predict housing prices.
  • Object Detection – A much more advanced yet simple case study that will guide you toward making a machine learning model that can detect objects in real-time.
  • Stock Market Analysis – Using historical stock market data, you will learn about how feature engineering and feature selection can provide you with some really helpful and actionable insights for specific stocks.
  • Banking Problem – A classification problem that predicts consumer behavior based on various features using machine learning models.
  • AI Chatbot – Using the NLTK python library, you will be able to apply machine learning algorithms and create an AI chatbot.
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  • LSTM – What is LSTM?, How does LSTM work, Applications of LSTM, etc.
  • Transformers – What are transformers, how does a transformer work in deep learning, applications of transformers, types of transformers, encoder-decoded, self-attention, etc.
  • BERT – Language Models, What is BERT, How does BERT work, how is BERT different from LSTM, applications of BERT, etc.
  • GPT – What are generative pre-trained models (GPT), how does a GPT work?, real life examples of GPT, etc.
  • LLM – NLP and Language models, what are LLMs, how does a LLM work, applications of LLM, etc.
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Elective

Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data.

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Introduction to MLOps 

  • MLOps lifecycle
  • MLOps pipeline 
  • MLOps Components, Processes, etc

Deploying Machine Learning Models 

  • Introduction to Azure Machine Learning 
  • Deploying Machine Learning Models using Azure
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Version Control 

  • What is version control, types, SVN.

GIT

  • Git Lifecycle, Common Git commands, Working with branches in Git
  • Github collaboration (pull request), Github Authentication (ssh and Http)
  • Merging branches, Resolving merge conflicts, Git workflow
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  • Job Search Strategy
  • Resume Building
  • Linkedin Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test.
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Excel Fundamentals 

  • Reading the Data, Referencing in formulae , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering 
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security 
  • VBA Macros, Ranges and Worksheet in VBA 
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.  

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve 
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence 
  • Mutual Information 

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions 
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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Data Science Course Projects

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

class-notifications
Hackathons
career-services
major-announcements
collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your up upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & LinkedIn profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Data Science Certification

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The Data Science courses offered aim to upskill millions of students and professionals in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

Upon completion of this course, you will:

  • Receive an Advanced Certification in Data Science and AI from iHUB IIT Roorkee ( An Innovation Hub of IIT Roorkee). Receive live lectures from IIT Faculty & Industry Experts

Key achievements of IIT Roorkee:

  • Ranked 7th ‘Overall’ and 6th in ‘Engineering’ in India as declared by NIRF 2022
  • Ranked 175th in the world for ‘Engineering and Technology’ by QS World University Rankings 2023
  • Ranked as the 369th best institute in the world by QS World University Rankings 2023
  • Ranked as the 114th best institute in Asia by QS World University Rankings 2023

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Data Science Training in Raleigh FAQs

Why should I learn Data Science in Raleigh from Intellipaat?

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

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

Intellipaat is the leading course provider in Raleigh. Our e-learning institute center delivers exceptional courses in  Data Analytics, Python, Artificial Intelligence, Machine Learning, Python for Data Science, R programming language, Business Analytics, and others to help you gain full control of your Data Science career path.

This online training is created by experienced Data Scientists from India and the United States. The course is designed to be easily understood, even for those without a technical background or much knowledge in this area. We also provide practical learning through real projects, making it accessible for newcomers.

Intellipaat does not directly send 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 good job in the Data Science domain.

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.

To learn Data Science for free, you need to look at the blogs and YouTube videos published by Intellipaat. Read the top-recommended blogs on their Interview Questions, Tutorial, and everything about Data Science.

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 objective 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 different industry-based projects. The teaching assistance provided by Intellipaat is only available during standard hours.

Since it involves various aspects of advanced technologies, such as Machine Learning, Artificial Intelligence, Deep Learning, and among others, it is comparatively difficult to learn. However, this Data Science online training is offered by IIT Roorkee faculty and Industry experts 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.

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, this Data Science online training is offered by IIT Roorkee faculty and Industry experts 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.

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 Multinational companies from around the world and some of the Fortune 500 companies.

If you wish to enroll in our Data Scientist training in Raleigh, 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 option.

Intellipaat provides one of the most affordable e-learning providers today. This Data Science online training in Raleigh costs ₹85,044.

No Cost EMI options are available. For more detailed information, contact our team @ IN: +91-7022374614

For Intellipaat courses, geographical boundaries do not apply. It does not matter at all in whichever area of Raleigh you are, you can access our online course sitting at home or office.

We provide training in two categories:

  • Self-paced training
  • Online classroom training

The cost of the self-paced training mode is ₹15,048, and the online classroom training mode costs ₹22,743.

No Cost EMI options are available. For more detailed information, contact our team @ IN: +91-7022374614

If you’re looking for a discount on Intellipaat’s online training for your group, reach out to our course advisors. They’ll fill you in on all the details about the special offers related to your group’s size and type.

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 provides training with practical, real-world projects that are current, useful, and valuable. This helps you apply what you’ve learned in actual industry situations.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.

If you want to switch from learning on your own to having a teacher online, you just need to pay a little extra. You can join the very next batch, which will be duly notified to you.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of 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 support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance 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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