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PG Course in Data Science, Machine Learning & Neural Networks in collaboration with

Aligned to Competency Standards developed by SSC NASSCOM In Collaboration with Industry and approved by Government of India

Best Data Science Course India with Placement Guarantee

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Be an industry-ready Certified Data Scientist with this exclusive Data Science Course India by immersive learning of Data Analysis with Machine Learning models, NLP, Visualization, predicting Forecasting Models, Deep Learning & more with a 100% placement guarantee Program in India.

In Collaboration With
  • NASSCOM
    in
    India
  • nasscom data science course india

21 Jun, 2024

Next Batch
starts on

12 Months

Recommended
20-22 hrs/week

6 Months

Live
Internship

Online

Learning
Format

6000+

Career
Transformed

950+

Hiring
Partners

Course Description

Data Science Course in India

DataTrained offers the Best Data Science Course in India where you get hands-on training on all relevant and in-demand tools, learn 14+ programming tools & languages, techniques, Data Mining, Data Collection, Data Extraction, Data Cleansing, Data Exploration, fundamentals viz., (calculations, data sets, manipulation), statistical concepts (mean, median, mode, standard deviation and skewness) along with real-world scenarios applied for data analysis using graphs/charts. Apart from that, this course also builds programming skills including code solutions, algorithms and flowcharts/pseudocode.., and technologies from this Data Science Course in India with Placement. Also with the most affordable Data Science Course in India fees structure. DataTrained is regarded as the best Data Science training institute in India which offers services from training to placement guarantee. DataTrained imparts the Best Data Science Course in India with placement guarantee. Enroll Now, to start your career with this Data Science Course in India with placement guarantee.

Key Highlights

  • 6 Months of rigorous Internship - data science course india6 Months of rigorous Internship
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  • 40+ Live Projects along with Case Studies - data science course india40+ Live Projects along with Case Studies
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PG Program in Data Science, Machine Learning & Neural Networks

  1. ₹ 160000 + 18% GST
    • Learners - data science course india
    • Learners - data science course india
    • Learners - data science course india
    • Learners - data science course india
    8500+ learners
Features
  • 300+ hours of learning
  • Practice Test Included
  • Certificate of completion
  • 5 Domain Specializations

12 Months PG Program in Data Science, Machine Learning & Neural Networks in collaboration with

Get eligible for 4 world-class certifications thus adding that extra edge to your resume.

  • Course completion certificate from NASSCOM
  • Project Completion Certificate from DataTrained Education
  • Course completion certificate from DataTrained Education
  • Internship Certificate from Partner Companies

Inclusion of every languages and tools that are covered.

  • Excel Best Data Science Course in Delhi
  • Python Best Data Science Course in Delhi
  • SQL server Best Data Science Course in Delhi
  • Applied Statistics Best Data Science Course in Delhi
  • numpy Best Data Science Course in Delhi
  • Pandas Best Data Science Course in Delhi
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Detailed Syllabus of Data Science Course India

  • 300+ Hours of Content - data science program institute
  • 300+

    Hours of Content

  • 80+ Live Sessions - data science online training
  • 80+

    Live Sessions

  • 15 Tools and Software - best tools for data science
  • 15

    Tools and Software

Comprehensive Curriculum

The curriculum has been designed by faculty from IITs, and Expert Industry Professionals.

300+ Hours of Content - data science program institute
300+

Hours of Content

80+ Live Sessions - data science online training
80+

Live Sessions

15 Tools and Software - best tools for data science
15

Tools and Software

Set the Basics Right

DataTrained's orientation prepares students to use the platform by introducing the Learning Management System, accessing course material, attending live classes and assessments, connecting with mentors and receiving career coach support. A preparatory session covers curriculum explanation and software installation guidance. The Data Science Foundation course covers Excel fundamentals (calculations, data sets, manipulation) and statistical concepts (mean, median, mode, standard deviation and skewness) with real-world scenarios applied for data analysis using graphs/charts. The Programming Foundation course introduces data science and builds programming skills including code solutions, algorithms and flowcharts/pseudocode for further exploration of data science/coding.

The orientation session at DataTrained is tailored to equip students with the necessary information and understanding to effectively utilize our platform for the best possible outcome. During this session, students are provided with a thorough introduction to our modern Learning Management System, called the DataTrained Academy. Students gain an understanding of how they can easily access course material, engage in live classes, complete assessments, and connect with mentors for any questions or queries. Moreover, students learn about the career coach support who is available to them throughout their course journey to provide guidance and support.

In order to ensure that students have a comprehensive understanding of the course and its expectations, a preparatory session is held prior to the commencement of the program. This session is designed to give students an in-depth explanation of the entire curriculum, as well as guidance on how to install any necessary software needed to begin their journey with the course. This preparatory session helps to alleviate any uncertainties or apprehensions that students may have about their upcoming program, and ensures that they are fully prepared for the challenges ahead.

The "Data Science Foundation" course is the next offering in the program, allowing students to gain insight into data science and the responsibilities of a data scientist or analyst. It begins with a thorough overview of Excel fundamentals, such as basic calculations, working with data sets, cleaning and manipulating it for further use. Additionally, learners will be introduced to important statistical concepts like mean, median, mode, standard deviation and skewness. They will also be coached on how to apply these to real-world scenarios in Excel and analyze data accurately. Through the use of graphs and charts, students can then make informed decisions based on their observations from the data analysis.

Upon being given a basic introduction to the expansive field of data science, students build upon their programming skills through the "Programming Foundation for Data Science" course. Its primary purpose is to ensure that students have a thorough understanding of programming fundamentals and how to create a code-based solution for any problem or challenge they may face. Throughout this course, students acquire the ability to craft algorithms by way of flowcharts and pseudocode, which are essential components in any programming journey. This course provides an excellent foundation for those looking to explore the world of data science and coding practices in greater detail.

Foundations

The Foundations bundle comprises 2 courses where you will learn to tackle Statistics and Coding head-on. These 2 courses create a strong base for us to go through the rest of the tour with ease.

This course will introduce you to the world of Python programming language that is widely used in Artificial Intelligence and Machine Learning. We will start with basic ideas before going on to the language's important vocabulary as search phrases, syntax, or sentence building. This course will take you from the basic principles of AI and ML to the crucial ideas with Python, among the most widely used and effective programming languages in the present market. In simple terms, Python is like the English language.

Python Basics

Python is a popular high-level programming language with a simple, easy-to-understand syntax that focuses on readability. This module will guide you through the whole foundations of Python programming, culminating in the execution of your 1st Python program.

Anaconda Installation - Jupyter notebook operation

Using Jupyter Notebook, you will learn how to use Python for Artificial Intelligence and Machine Learning. We can create and share documents with narrative prose, visualizations, mathematics, and live code using this open-source online tool.

Python functions, packages and other modules

For code reusability and software modularity, functions & packages are used. In this module, you will learn how you can comprehend and use Python functions and packages for AI.

NumPy, Pandas, Visualization tools

In this module, you will learn how to use Pandas, Matplotlib, NumPy, and Seaborn to explore data sets. These are the most frequently used Python libraries. You'll also find out how to present tons of your data in simple graphs with Python libraries as Seaborn and Matplotlib.

Working with various data structures in Python, Pandas, Numpy

Understanding Data Structures is among the core components in Data Science. Additionally, data structure assists AI and ML in voice & image processing. In this module, you will learn about data structures such as Data Frames, Tuples, Lists, and arrays, & precisely how to implement them in Python.

In this module, you will learn about the words and ideas that are important to Exploratory Data Analysis and Machine Learning. You will study a specific set of tools required to assess and extract meaningful insights from data, from a simple average to the advanced process of finding statistical evidence to support or even reject wild guesses & hypotheses.

Descriptive Statistics

Descriptive Statistics is the study of data analysis that involves describing and summarising different data sets. It can be any sample of a world's production or the salaries of employees. This module will teach you how to use Python to learn Descriptive Statistics for Machine Learning.

Inferential Statistics

In this module, you will use Python to study the core ideas of using data for estimating and evaluating hypotheses. You will also learn how you can get the insight of a large population or employees of any company which can't be achieved manually.

Probability & Conditional Probability

Probability is a quantitative tool for examining unpredictability, as the possibility of an event occurring in a random occurrence. The probability of an event occurring because of the occurrence of several other occurrences is recognized as conditional probability. You will learn Probability and Conditional Probability in Python for Machine Learning in this module.

Hypothesis Testing

With this module, you will learn how to use Python for Hypothesis Testing in Machine Learning. In Applied Statistics, hypothesis testing is among the crucial steps for conducting experiments based on the observed data.

Machine Learning

Machine Learning is a part of artificial intelligence that allows software programs to boost their prediction accuracy without simply being expressly designed to do so. You will learn all the Machine Learning methods from fundamental to advanced, and the most frequently used Classical ML algorithms that fall into all of the categories.

With this module, you will learn supervised machine learning algorithms, the way they operate, and what applications they can be used for - Classification and Regression.

Linear Regression - Simple, Multiple regression

Linear Regression is one of the most popular Machine Learning algorithms for predictive studies, leading to the very best benefits. It is an algorithm that assumes the dependent and independent variables have a linear connection.

Logistic regression

Logistic Regression is one of the most popular machine learning algorithms. It is a fundamental classification technique that uses independent variables to predict binary data like 0 or 1, positive or negative , true or false, etc. In this module, you will learn all of the Logistic Regression concepts that are used in Machine Learning.

K-NN classification

k-Nearest Neighbours (Knn) is another widely used Classification algorithm, it is a basic machine learning algorithm for addressing regression and classification problems. With this module, you will learn how to use this algorithm. You will also understand the reason why it is known as the Lazy algorithm. Interesting Right?

Support vector machines

Support Vector Machine (SVM) is another important machine learning technique for regression and classification problems. In this module, you will learn how to apply the algorithm into practice and understand several ways of classifying the data.

We explore beyond the limits of supervised standalone models in this Machine Learning online course and then discover a number of ways to address them, for example Ensemble approaches.

Decision Trees

The Decision Tree algorithm is an important part of the supervised learning algorithms family. The decision tree approach can be used to resolve regression and classification problems unlike others. By learning simple decision rules inferred from previous data, the goal of using a Decision Tree is constructing a training type that will be used to predict the class or value of the target varying.

Random Forests

Random Forest is a common supervised learning technique. It consists of multiple decision trees on the different subsets of the initial dataset. The average is then calculated to enhance the dataset's prediction accuracy.

Bagging and Boosting

When the aim is to decrease the variance of a decision tree classifier, bagging is implemented. The average of all predictions from several trees is used, that is a lot more dependable than a single decision tree classifier.

Boosting is a technique for generating a set of predictions. Learners are taught gradually in this technique, with early learners fitting basic models to the data and consequently analyzing the data for errors.

In this module, you will study what Unsupervised Learning algorithms are, how they operate, and what applications they can be used for - Clustering and Dimensionality Reduction, and so on.

K-means clustering

In Machine Learning or even Data Science, K-means clustering is a common unsupervised learning method for managing clustering problems. In this module, you will learn how the algorithm works and how you can use it.

Hierarchical clustering

Hierarchical Clustering is a machine learning algorithm for creating a bunch hierarchy or tree-like structure. It is used to group a set of unlabeled datasets into a bunch in a hierarchical framework. This module will help you to use this technique.

Principal Component Analysis

PCA is a Dimensional Reduction technique for reducing a model's complexity, like reducing the number of input variables in a predictive model to avoid overfitting. Dimension Reduction PCA is also a well-known ML approach in Python, and this module will cover all that you need to know about this.

DBSCAN

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is used to identify arbitrary-shaped clusters and clusters with sound. You will learn how this algorithm will help us to identify odd ones out from the group.

Advanced Techniques

EDA - Part1

Exploratory Data Analysis (EDA) is a procedure of analyzing the data using different tools and techniques. You will learn data standardization and represent the data through different graphs to assess and make decisions for several business use cases. You will also learn all the essential encoding techniques.

EDA - Part2

You will also get a opportunity to use null values, dealing with various data and outliers preprocessing techniques to create a machine learning model.

Feature Engineering

Feature Engineering is the process of extracting features from an organization's raw data by using domain expertise. A feature is a property shared by independent units that can be used for prediction or analysis. With this module, you will learn how this works.

Feature Selection

Feature selection is also called attribute selection, variable selection, or variable subset selection. It is the process of selecting a subset of relevant features for use in model development. You can learn many techniques to do the feature selection.

Model building techniques

Here you will learn different model-building techniques using different tools

Model Tuning techniques

In this module, you can learn how to enhance model performance using advanced techniques as GridSearch CV, Randomized Search CV, cross-validation strategies, etc.

Building Pipeline

What is Modeling Pipeline and how does it work? Well, it is a set of data preparation steps, modeling functions, and prediction transform routines organized in a logical order. It allows you to specify, evaluate, and use a series of measures as an atomic unit.

Time Series Analysis

Introduction

A time series is a set of data points that appear in a specific order over a specific time. A time series in investing records the movement of selected data points, like the cost of security, with a set period of time, with data points collected at regular intervals.

Time Series Components

In this module, you will learn about different components that are necessary to analyze and forecast future outcomes.

Stationarity

You will learn what is stationarity and the importance of learning stationarity.

Time Series Models

In this module, you will learn common Time series models as AR, MA, ARIMA, etc.

Model Evaluation

When you build models, you will use different evaluation methods to gauge the product performance or even accuracy. Yes, In this module, you will learn model evaluation methods.

Use Case and Assignment

You will also get a chance to work on assignments and feel at ease while working on the use case scenarios.

Projects

Also, we are providing a few more extra projects for practice, you can assemble and compare your solutions with the ones we provide.

Recommendation Engine

Introduction

In the introduction module, you will learn why recommendation systems are used, their requirement, and their applications.

Understanding the relationship

In this module, you will learn on what basis recommendation engine works and their association rules.

Types of Data in RS

In this module, you will learn all the types of data used in the Recommendation Engine.

Ratings in RS

In this module, you will learn just how the ratings are drawn in the Recommendation Engine.

Similarity and Its Measures

Recommendation systems work on the basis of similarity between the product and the consumers who view it. There are many ways for determining how similar 2 products are. This similarity matrix is used by recommendation systems to recommend the next most comparable product to the customer.

Types of Recommendation Engine

In this module, you will learn different types of Recommendation Engines.

Evaluation Metrics in Recommendation

Once you build the models, you require metrics to evaluate how effective is your model. You will learn various evaluation tools in RE.

Use cases

You will also get an opportunity to focus on additional use cases. Later, you can compare your solution with the SME-provided solution.

ChatGpt Essentials

ChatGpt is a revolutionary AI chatbot technology that provides users with powerful tools for content generation, prompt ideas, and other features. This module will help you understand the various capabilities of this advanced technology, including its strengths and limitations.

GPT-3 (Generative Pre-trained Transformer 3) is a state-of-the-art language model developed by OpenAI. Learn about GPT-3 and its capabilities like Natural Language Understanding abd Promt Engineering.

Prompt engineering is the practice of designing and crafting effective prompts or input instructions for language models like GPT-3 to guide their generation of desired outputs. Learn to leverage the power of prompt engineering to be 10x productive like never before.

Explainable AI and model interpretability are becoming increasingly important as AI models are being used in various critical domains, such as healthcare, finance, and legal systems, where accountability, fairness, and transparency are crucial. Learn to build machine learning models using LIME & ShARP.

Dive into the GPT model and their architecture. Develop understanding about concepts like Reinforcement Learning from Human Feedback (RLHF), one-shot learning, and few shot learning.

Learn to build an AI Evaluator that automatically evaluate exam submissions by the students by leveraging the GPT and eliminating the need for training NLP models from the scratch.

Understand and learn to build a GNN model.

In depth understanding of advanced GNN.

Generative models can be used in a wide range of applications, including image generation, text generation, speech synthesis, music composition, and more. Build underderstandinng of text-to-image models and image-to-text models.

Electives

Strong hand-holding with dedicated support to help you master some of the complex processes of Data Science and Artificial Intelligence.

Deep Learning with Computer Vision

  • Deep Learning
  • Computer Vision

Deep Learning with NLP

  • Deep Learning
  • Deep NLP

Business Analytics with R

  • Business Analytics with "R" programming and R shiny
  • Business Analytics with Advanced Excel

Business Analytics with Tableau

  • Business Analytics with Tableau
  • Business Analytics with Advanced Excel

Business Analytics with Power BI

  • Business Analytics with Power BI
  • Business Analytics with Advanced Excel
data science course in delhi fees

Next Batch Start

21 Jun, 2024

66% Average Salary Hike - data science course india 66%

Average Salary Hike

Upto 25LPA Highest Salary - data science course india Upto 25LPA

Highest Salary

7k+ Jobs Sourced  - data science course india 7k+

Jobs Sourced

950+ Hiring Partners  - data science course india 950+

Hiring Partners

Instructors

Join DataTrained – Certified curriculum and learn every skill from the industry’s best thought leaders.

Dr. Deepika Sharma - Training Head, DataTrained

Dr. Deepika Sharma

Training Head, DataTrained

Dr. Deepika Sharma has been associated with academics /corporate education for more than 14 years. She has a deep passion in the field of Artificial Intelligence, Data Science, and Machine Learning.

Shankargouda Tegginmani - Data Scientist, Accenture

Shankargouda Tegginmani

Data Scientist, Accenture

Shankar is a data Scientist with 14 Years of Experience. His current employment is with Accenture and has experience in telecom, healthcare, finance and banking products.

Andrew Labeodan - Data Scientist, Centrica

Andrew Labeodan

Data Scientist, Centrica

Andrew is a data Scientist with 14 years of experience. His expertise spans healthcare and Energy Utilities, and he's renowned for successfully implementing data analytics in oncology.

Adedolapo Ogunlade - Data Scientist at Kaggle

Adedolapo Ogunlade

Data Scientist at Kaggle

Adedolapo is a seasoned Data Scientist at Kaggle, specializing in Machine Learning, Statistical Analysis, Data Visualization, and Data Science.

Gifty Aiyegbeni - Data Scientist at Bincom Global

Gifty Aiyegbeni

Data Scientist at Bincom Global

Gifty is a dedicated data scientist and analyst passionate, currently working in Bincom Global. She is experienced in python programming, R programming, and SQL queries while offering knowledge in statistical analysis.

Ioannis Petridis - Data Scientist at KLDiscovery

Ioannis Petridis

Data Scientist at KLDiscovery

Ioannis Petridis is Data Scientist with 9+ years of experience, currently working in KLDiscovery. He has a deep passion in apply lean Data Science and Machine Learning solutions to solve business problems and deliver impactful and innovative products.

Why DataTrained For Data Science Course India?

DataTrained provides the most exclusive and the best Data Science course in India with 100% placement guarantee, i.e., the PGP in Data Science, Machine Learning, and Neural Networks. One of the top Data Scientists develop the Program from and industry experts working in the data science companies of India for several decades, and the course curriculum is at par with the international industry standards. The program duration is 12 months, which perfectly balances practical and theoretical learning, covering everything from the basic to the advanced levels of the Data Science course India with placement across India.

Enroll today in the Best Data Science online course India with placement.

5 Unique Specializations - data science course india

5 Unique Specializations

Get a chance to select from five unique specializations as per your career aspirations & academic background. Obtain an Executive Certificate In Data Science, ML, and Neural Networks In Collaboration With in India.

Dedicated Career Assistance - data science course india

Dedicated Career Assistance

Get a chance to get 1:1 career counseling meetings from industry experts and regular extensive mock interviews with hiring managers. uplift your career with our 950+ hiring partners from many industry domains.

Student Support - data science course india

Students Support

Chat support is open from morning 06 AM to 11 PM IST for instant Query Resolution. Our Program Managers are always available on call or chat 24*7, & you can also use our user-friendly ticket-raising system during company hours.

Career Impact

DataTrained has collaborated with and delivers the best online Data Science course in India. Over 150,000+ Careers Transformed till now and still counting.

DataTrained has supported me with the censorious knowledge and learning skills required for a data scientist position. The trainer starts with a good example to make everyone understand the concept and then helps us construct the Algorithms with the real industry data sets. DataTrained brings the ability of online learning and dedicated Mentorship, Counseling, Live Sessions, and six months Internships.

Aaruni Khare, Data Scientist, RBS - data science course india
Aruni Khare Data Scientist, RBS

I saw an ad on Facebook of DataTrained, and contacted them immediately & enquired about their Data Science course. The counselor of data trained took me through the entire journey of what they give and what data science is all about. After continued conversation for 2-3 weeks, I was relatively sure about the data science course, and now I definitely knew where I needed to invest money, time and hard work.

Rakshit Jain, Data Scientist, Optum - data science course india
Rakshit Jain Data Scientist, Optum

The program is a well-balanced blend of recorded classes, weekend live sessions, & hardcopy reading materials they sent on my address. My mentor was Amit Kaushik that time, and he assisted me in getting that confidence and complete my assignments in time. I have almost the course and have been able to crack the Glenmark interview in Mumbai. Thank you so much, DataTrained.

Rupam Kumar Chaurasia, Head Sales, Glenmark - data science course india
Rupam Kumar Chaurasia Head Sales, Glenmark

Career Support

Internship - data science course india

With the Data Science course India, we offer a six Months internship to make sure that students graduate as experienced data science professionals and are no fresher. Datatrained also allows students to go for an online internship for working professionals.

Resume Feedback - data science course india

Datatrained has collaborated with IIMJobs for the Top Data science course India, which offers you access to their paid resume preparation tools and personal feedback from experts in the HR domain. Our experts prepare An individual career profile as per the candidate's experience to make sure it is relevant to a data science role.

Interview Preparation - data science course india

Regular mock test HR along with Technical interviews by the mentors with personal support and guidance to each and every student. The industry mentors ease students to take projects on Kaggle so that their resume looks competitive and professional to the recruiters.

Placement - data science course india

We generate each student's Ability to Score, which is then sent to our 950+ recruitment partner organizations. We arrange campus placements every 3 months to place our students in the best organizations.

Frequently Asked Questions

This PG program in data science, machine learning, and neural networks is the best data science course in India. This data science course India comes with a 100% placement guarantee or MONEY BACK GUARANTEE i.e if they fail to get you a job after successfully completing the course they will return your data science course India fees back post 6 months of course completion.

It is not essential to have a coding background, basic knowledge is sufficient. Although data science needs coding, you don’t need to be an expert in this. Python is one of the programs of data science. Python is like the English language. You just have an overview of the language. This data science course India comes with 6 months of life industrial internship which is offered by no other ed-tech platform.

Our aim is to provide the best data science course India, our data science fee structure is best compared to any other online platform. We offer a no-cost EMI payment option also. Our focus is to provide quality education in data science at the best price.

We aspire to place our students in the best organizations in India and abroad. foreign.it’s our job to make data science programs affordable for those who are interested in data science learning. For further queries please contact us. We would love to hear from you.

You can get a data science degree in India by completing this data science course India. The course duration is 12 months including 6 months of internship as the core of the data science course India. Our data science course India is in collaboration with i.e. data scientists from and experts from the data science domain have co-developed this data science course India.

150,000 aspirants had already started their dream jobs after completing this data science course India. The eligibility criteria for this data science course India are a bachelor’s degree in any stream and a basic understanding of statistics and mathematics. Undergraduate data science course India requires students to score more than 50% marks in class 12 exams with mathematics, statistics, or computer science as one of the major subjects.

We offer the best data science courses India with 100% placement guarantee. We have more than 400 hiring partners in India and across the globe. We organize campus placements every quarter. We promised and placed 350 students in only 15 days.an article is also published in the hindustan times. CLICK HERE

  • Efficient and extensive mock technical and HR interviews with immediate feedback & personal guidance
  • Resume building tools from IIM Jobs
  • Individual feedback on the resume by HR experts
  • 6 months live internship to ensure you obtain relevant experience

coperatively with a data science course India, we offer dedicated career assistance to our students. We have successfully transformed more than 150,000+ careers. You can be next! For more information, you can contact us.

The duration of this data science course India is 12 months including a six months of internship. This data science course India is developed in collaboration with to bridge the existing gap between the increasing demand of skilled data science professionals and the lack of skilled data science professionals in India and across the globe as well.

You are eligible for a refund of the Booking Amount if you cancel your course within 7 calendar days of the Course Registration Date, which is the date of payment. However, this refund policy does not supersede any course-specific refund terms. Please consult your counselor for more information about the respective course's refund terms.

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