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PG Program in Data Science, Machine Learning, and Neural Networks in India in collaboration with

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

Data Science in India with Placement Guarantee

In Curriculum

ChatGPT

Enrolled students will become an industry-ready and Certified Data Science professional with this exclusive Data Science in India by immersive training of Data Analysis with Machine Learning models, NLP, Visualization, Forecasting and predicting Models, Deep Learning & more with a 100% placement guarantee in India.

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

19 Jul, 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 Full Course in India

DataTrained offers the Best Data Science Full 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 Full 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 Online Course in India which offers services from training to placement guarantee. DataTrained imparts the Best Data Science Full Course in India with placement guarantee. Enroll Now, to start your career with this Data Analyst Course Online with placement guarantee.

Key Highlights

  • 6 Months of rigorous Internship - data science in india6 Months of rigorous Internship
  • One-on-One interaction with Industry Mentors - data science in indiaOne-on-One interaction with Industry Mentors
  • 100% Placement guarantee - data science in india100% Placement guarantee
  • 40+ Live Projects along with Case Studies - data science in india40+ Live Projects along with Case Studies
  • Dedicated Career Program Manager - data science in indiaDedicated Career Program Manager
  • 360 Degree Career Guidance - data science in india360 Degree Career Guidance
  • Ideal for both Fresh Graduates - data science in indiaIdeal for both Fresh Graduates & Working Professionals
  • Unique Specializations - data science in indiaUnique Specializations to choose from
  • Prompt Query Resolution - data science in indiaPrompt Query Resolution

PG Program in Data Science, Machine Learning & Neural Networks

  1. ₹ 160000
    • Learners - data science in india
    • Learners - data science in india
    • Learners - data science in india
    • Learners - data science in 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

Languages and Tools covered.

  • Excel - data science in india
  • Python - data science in india
  • Tableau - data science in india
  • NLP - data science in india
  • SQL server - data science in india

What's the focus of this Data Science in India with placement?

Enrolled students can select from 5 Unique specializations, learn 14+ programming tools & languages, Live case studies and projects, six months of live internship, get mentorship from industry experts, dedicated career support, & much more with the best data science in India.

5 Unique Specializations - data science in india

5 Unique Specializations

Get a chance to choose from five unique specializations as per your career aspirations and academic background. Get consultation from counselors to obtain an Executive Certification In Data Science, ML & Neural Networks In Collaboration With in India.

Dedicated Career Assistance - data science in india

Dedicated Career Assistance

Get a chance to Receive one on one career counseling sessions from industry experts & regular extensive mock interviews with hiring managers. Enhance your career with 950+ hiring partners from various industrial domains.

Student Support - data science in india

Students Support

Chat support for instant Query Resolution is open from 06 AM to 11 PM IST. To clarify doubts of students, program managers are always available, and you can also use our user-friendly ticket-raising system during company hours.

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.

Data Science Course Syllabus

Best-in-class content by leading faculty and industry leaders in the form of live sessions, pre-recorded videos, projects, case studies, industry webinars, and assignments.

best data science courses online

Detailed Syllabus of Data Science Course

  • 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

Industry Projects

Learn live experience industry projects supported by top companies across industries and the most exclusive data science in India.

  • Being involved in joint projects and learning from peers - data science in indiaBeing involved in joint projects and learning from peers
  • mentorship and apply learnings in a better way - data science in indiaLearn from industry professionals through their mentorship and apply learnings in a better way
  • Personalized and subjective feedback - data science in indiaWhile Personalized subjective feedback for your submissions to facilitate improvement
Smartphone and Smartwatch Activity - data science in india

Smartphone and The Smartwatch Activity

The Whirligig sensor & crude accelerometer info is gathered from the cell phone and smartwatch at a pace of 20Hz.

Recommendation System - data science in india

Recommendation System

Organizations must be used to Recommend their Products & Services to the People in the interconnected society.

Air Quality Study - data science in india

Air Quality Study

Forecasting The Air Quality Of Several Parts Of The Country by establishing the Data Collected from the Meteorological Department.

Why Choose DataTrained For A Data Science In India with Placement?

DataTrained provides the most exclusive Data Science in India with a 100% placement guarantee, i.e., the PG Program in Data Science, Neural Networks, and Machine Learning. Top Data Scientists develop this Program from and industry experts working in the data science companies of India for several decades, and the 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 fundamentals basic to the advanced levels of Data Science in India with placement across India.

Enroll today in the Best Data Science institute in India with placement.

Internship - data science in india

DataTrained provides you a 6 Months internship in Data Science in India, to ensure that students graduate and emerge as experienced data science professionals in the coming years and are no fresher. DataTrained also permits you to go for an online internship for working professionals.

Resume Feedback - data science in india

DataTrained work together with IIMJobs for the Top Data science in India to ensure that each and every enrolled student gets a high-paying job. Enrolled students have access to the paid resume preparation kit handled by IIMJobs and will get personal feedback from high experts from the HR domain. Our experts prepare an individual career profile as the candidate's experience to ensure it is relevant to a data science role.

Interview Preparation - data science in india

Frequent mock HR along with Technical interviews by mentors with personal support to each student. Students take projects on Kaggle under the guidance of industry mentors so that their resume looks competitive and professional to the recruiters.

Placement - data science in india

We generate each student's Ability Score, then sent to our 950+ recruitment partner companies. Campus placements are arranged every three months to place our students in the best organizations.

Career Impact

DataTrained, in collaboration with , offers online Data Science in India. Over 150,000+ Careers Transformed till now and still growing.

DataTrained has supported me with the crucial knowledge and skills required for a data scientist role. The trainer begins with giving real-world examples to make us understand the structure and then helps us build the Algorithms with the real-time industry data sets. DataTrained brings out the power of online learning and dedicated Mentorship, Counseling, Live Sessions, and six months Internships.

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

I saw an advertisement from DataTrained on Fb, and I contacted them immediately and enquired about their Data Science online. The counselor took me through the whole journey of what they offer, about in-depth knowledge on course structure and what data science is all about. After continued conversation for a few weeks, I was relatively sure, and now I knew where I needed to invest my money and hard work.

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

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

Rupam Kumar Chaurasia, Head Sales, Glenmark - data science in india
Rupam Kumar Chaurasia Head Sales, Glenmark
66% Average Salary Hike - data science in india 66%

Average Salary Hike

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

Highest Salary

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

Jobs Sourced

950+ Hiring Partners  - data science in india 950+

Hiring Partners

Admission Process

There are three simple procedures in the Admission Process, which are detailed below.

Step 1: Fill in a Query Form

Please fill up the Query Form, and after that one of our counselors will call you & understand your eligibility for data science in India.

Step 2: Get Shortlisted and Receive a Call

Our Admissions Team will check your form. Successfully qualified candidates, an Email will be sent to you confirming your admission to the program.

Step 3: Book your Seat and Start the Prep Course

Book your seat with the payment to register for the program. Start with your Prep and start your Data Science journey!

Data Science Course Fee

₹ 160000 + GST

No Cost EMI options are also available. *

data science in india fees

I’m interested in this program

What's Included in the Price

Placements

Access to real-life 40 industry projects

6 Months online Internship part of the core curriculum

For Queries and Suggestions

Call DataTrained Now
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Data Science Trends in India

Covid - 19 Pandemic changed everything overnight, Massive demand for new innovations, and technologies were globally in need. According to Deloitte, data science is taking shape with a new standpoint after covid-19. Data analysts and data scientists are the most searched experts. Data science come up as the most producing sector after the pandemic. According to a blog, the use of cloud services for big data comes out as a major data management trend and the list goes on with the use of augmented analytics, hybrid cloud services, Hyper Automation, use of big data in IoT platforms, Quantum computing of faster analysis, AutoML, blockchain in data science. Data science will continue to be in trend in the following years.

Vacancies/Job in the field of Data Science in India

India is witnessing the rapid digitization of industries, making it the world's second-largest hub for data science. According to the World economic forum, Data analysis and data scientist will emerge as the no.1 leading role. Data science is one of the high-paying jobs. According to naukri.com data the variation of salary can be seen according to experience and location where you are pursuing a job follows; the average salary of a candidate with one year experience i.e, INR6.7LPA.

70% of these vacancies are for professionals with five years of experience. However, Companies are ready to pay a heavy salary to hire the best data scientist.

Data Science jobs/vacancies increased by 30% in April 2022 compared to April 2021. It revealed that demand for jobs in the data science profession is rising year-on-year and python secured first with the most demanding skill set, followed by java/javascript. Transitioning a career to data science is smart as it fetches far higher comparative returns.

Salary in India for Data Science Professionals

Data Scientist salary in India ranges from ₹4 Lakhs to ₹22.1 Lakhs, with an average annual salary of ₹10.4 Lakhs. When you get Your PG certificate, you can expect anywhere from a 13 to 25% enhancement in your yearly wage.

Thus, investing just 4-5 hours weekly of time to gain specialization in Data Science and Machine Learning gives high compounded returns, in the long run, allowing professionals to expand their career horizons.

Data Science in India

The industrial revolution of India is at its peak and playing a major role in transforming India towards digitalization. To achieve targets of digitalization, the Government of India started an umbrella program-Digital India. This initiative made online availability of all government services for citizens with better internet connectivity by online friendly infrastructure. Digital India empowers its citizens by providing digital power. With the increase in digitalization, the massive need for data science in India is increasing day by day. In India, there are many highest-paid cities those are:

Frequently Asked Questions

If you're looking for the best data science institute then you should choose Data trained. They are setting up a new bar with different models, and specializations. The student can register it from anywhere, anytime at your convenience. The course is designed for working professionals as well as freshers.

The data science course of Data trained is in collaboration with . By using big data tools you will learn to handle big data. They are coming up with providing mentorship from Industrial experts plus 6 months of internship, you will work on real-time industry projects. Also, the query resolution is very effective. You can raise tickets and doubts will be solved instantly by the professionals.

Yes, Data science is a promising career and there is a big reason behind it. Today, we are surrounded by a huge chunk of data. We can make this data meaningful and can get useful insights to predict future trends through Data science. The Future of Data science is bright today and will evolve in the coming years. If someone is planning to learn Data science or planning to shift his/her career path toward this field, will definitely see fruitful results.

Yes, this data science course in India comes with a placement guarantee or money Back challenge. Money back challenge means if a student will not be placed, his/her whole fees will be refunded. You may wonder, why are we so confident about this challenge? It’s because we map out our syllabus in such a way that there is not any loophole. There will be a 6 months live internship.

You will be able to solve real-world problems. Projects will be real-time industrial projects. You will no longer be called a fresher. The fresher tag will be removed from your resume and you will be industry ready. Learning based on projects is the need of the hour, that’s why we come up with 40+ projects, 20 will be assessment projects, and 20 will be evaluation projects. Mentors will be available for you to review your projects and solve your doubts while working on projects.

Yes, any aspiring individual can become a data scientist with this data science course in India. Any aspiring student can learn all the fundamentals in 10-12 months by dedicating around 4-5 hours a day. No prior experience in coding is required however if you have some basic understanding of language, it will be a plus. The syllabus of The Data Science course by Data Trained comprises all necessary coding skills needed to become a Data scientist.

There are a lot of options to choose a data science course. Online courses are more affordable than offline ones. Many institutes are offering data science courses. Data science course fees depend on the type of the institute. Some institutes are charging very high fees ranging from 5-12Lakh. Some specific institutes have affordable fee structures. Data trained course is one of the affordable and pocket-friendly courses. Data science course fees by Data Trained.

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.