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PG Program in Data Analytics in
collaboration with IBM

Become an industry-ready Certified Data Analytics professional by completing this course and learning about each concept, tool, and technology of Data Analytics. Be ready to work as a Data Analytics Engineer after completing the course.

Program Overview

You will learn everything about in-demand technologies of Data Analytics from beginning to expert level. Analyze the Real-Time Industries Big Data with expert analysts and get your dream job at the end of the course.

Key Highlights

  • One-on-One with industry mentorsOne-on-One with industry mentors
  • 100% Placement Assistance100% Placement Assistance
  • 360 Degree Career Support360 Degree Career Support
  • Instant Doubt ResolutionInstant Doubt Resolution
  • Ideal for both Working Professionals and Fresh GraduatesIdeal for both Working Professionals and Fresh Graduates
  • Interactive LearningInteractive Learning

PG Program in Data Analytics in collaboration with IBM

  1. 100000
    • Best online Data science course
    • Best online Data science course
    • Best online Data science course
    • Best online Data science course
    11500+ learners
Features
  • 350+ hours of learning
  • Practice Test Included
  • Certificate of completion
  • Instant Doubt Resolution

Languages and Tools covered

  • Excel in Data Science program - online excel course
  • python in Data Science Program - online python course
  • tableau in Data Science program - online tableau course
  • NLP in Data Science - online NLP course
  • SQL in Data science course - online SQL course

8 Months PG Program of Data Analytics in Collaboration with IBM

Get elligible for 3 world-class certificates thus adding that extra edge to your resume

  • Learning paths and certification from IBM
  • Course completion certificate from DataTrained Education
  • Project completion certificate from DataTrained Education

What’s the focus of this course?

The course is developed to make our students job-ready industry-level Data Analysts. With expert tutors and a smooth course structure, this course will help you in becoming a beginner to expert level Data Analytics Engineer and achieve your goal.

6 Unique Specializations- data science programs near me

Learn Anything, Anytime, Anywhere

Learn through our HD online videos by world class faculties and industry experts

Dedicated Career Assistance- data science program institute

Dedicated Career Assistance

Receive 1:1 career counseling sessions & mock interviews with hiring managers. Exhilarate your career with our 400+ hiring partners.

Student Support -  data science online training

Student Support

Chat support for Quick Doubt Resolution is available from 06 AM to 11 PM IST. Program Managers are available on call, chat and ticket during business hours.

Instructors

Join DataTrained -- IBM -- 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 10 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.

Sanket Maheshwari - Data Scientist, Faasos
Sanket Maheshwari
Data Scientist, Faasos

Experienced Data Scientist with a demonstrated history of working in the information technology and services industry.

Polong Lin - Business Analyst, IBM
Polong Lin
Business Analyst, IBM

Polong Lin is a Data Scientist at IBM in Canada. Under the Emerging Technologies division, Polong is responsible for educating the next generation of data scientists through BDU.

Jay Rajasekharan- Data Scientist, IBM
Jay Rajasekharan
Data Scientist, IBM

Currently, he is driving several productivity programs - using data analytics to drive insights from business operations and implementing optimizations such as streamlining workflows, improving service levels, and ultimately reducing cost.

Mahdi Noorian- Data Scientist, IBM
Mahdi Noorian
Data Scientist, IBM

Mahdi Noorian is a Postdoctoral Fellow at the Laboratory for Systems, Software and Semantics (LS3) of the Ryerson University. He holds a Ph.D degree in Computer Science from University of New Brunswick.

SYLLABUS

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

best data science courses online

Syllabus

Module 1 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.

Module 2 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.

Module 4 Tableau
Getting Started

Tableau is a visual platform for business intelligence and analytics which allows users to monitor, comprehend, observe, and make choices with a range of data. It allows you to produce any kind of graph, plot, or chart without scripting.

Data handling & summaries

You can learn how to handle various types of data, plot, analyze, sort, and summarise the entire data.

Building Advanced Reports/ Maps

Tableau Reports are a built-in feature of Tableau that allows users to display data from different sources into reports to better comprehend how far they have progressed toward their goals, better understand their customers' needs, and forecast future plans.

Calculated Fields

You will use calculated fields to generate new data from existing data in your data source. When you build a calculated field in your data source, you are efficient in including a new field (or column) whose values or members are determined by a computation that you control.

Table calculations

Table computations are modifications that can be applied to the data in a display. They are a kind of calculated field that works with Tableau's local data based on what is already in view.

Parameters

Parameters let you change a reference line, band, or box dynamically. For instance, reference a parameter rather than a reference line at a defined position on the axis. The reference line could be moved using parameter control.

Building Interactive Dashboards

An interactive dashboard allows you to dive down and filter operational data, allowing you to see data from multiple angles or in more depth. Dashboards allow data-driven business choices by providing a simplified and clear overview of overall business information.

Building Stories

A narrative in Tableau is a set of visuals that work together to present data. You can use tales to convey a data story, offer context, display how steps affect results or make a strong argument.

Working with Data

In this module, you will learn to join the tables, data blending and make connections, etc.

Sharing work with others

In this module, you will learn to share Workbooks, Publish to Reader/PDF and Publish to Tableau Server and share on the web.

Comprehensive Curriculum

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

100+ Hours of Content--- data science program institute
350+

Hours of Content

100+ Live Sessions--  data science online training
100+

Live Sessions

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                        Tools and Software- best tools for data science
15

Tools and Software

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Industry Projects

Real Time industry projects are covered that are running in Top MNC's of India with the interaction of expert software developers.

  • Data science program Engage in collaborative projects and learn from peers
  • Data science programMentoring by industry experts to learn and apply better
  • Data science programPersonalized subjective feedback on your submissions to facilitate improvement
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Smartphone and Smartwatch Activity

The crude accelerometer and whirligig sensor information is gathered from the cell phone and smartwatch at a pace of 20Hz.

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Recommendation System

In the connected world, it is imperative that the organizations are using to Recommend their Products & Services to the People.

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Air Quality Study

Based on The Data Collected from the Meteorological Department, Predicting The Air Quality Of Different Parts of The country

Why DataTrained for Data Analytics Course in India?

DataTrained offers an exclusive Data Analytics course in which it provides Expertise Tutors, Latest Tools and Technologies, Best Fee Structure, Real-Time Project Experience, 100% Job Assurance all these at affordable fees which makes it the best Data Analytics course available till date.

Resume pepration by DataTrained

Partnered with IIMJobs wherein you get access to their paid resume preparation kit and personal feedback from the industry HR experts. An individual career profile is prepared by our experts so that it suits his/her experience and makes it relevant to a Data Scientist role.

Interview pepration DataTrained

Regular mock HR and Technical interviews by mentors with personal guidance and support. The industry mentor helps learners to take projects on Kaggle and move on to the status bar so that their resume looks competitive to the recruiters.

100% granted placement

We generate the Ability Score of every individual which is then sent to our more than 400+ recruitment partner organizations. At last, we organize campus placements quarterly in Noida, Gurgaon, Ahmedabad, Bangalore, and Chennai to place our students.

Career Impact

DataTrained in collaboration with IBM presents the best online Data Analytics in India. With 10,000+ careers transformed.

DataTrained has helped me with the vital knowledge and skills that are needed for a data scientist role. The trainer starts with an example to make us comprehend the concept and then help us build the Algorithms with the real industry datasets.DataTrained brings the power of online learning along with dedicated Mentorship, Counselling, Live Sessions and 6 months Internship.

Aaruni Khare-- Data Scientist
Aaruni Khare
Data Scientist

I saw an ad from DataTrained on facebook and I contacted them straight away and enquired about their Data Science online course. Their counselor took me through the complete journey of what they offer and what is data science all about. After continuous conversation for a few weeks, I was pretty sure about the course and now I knew where I need to invest my money and hard work.

Rakshit Jain- Data Scientist, Optum
Rakshit Jain
Data Scientist, Optum

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

Rupam Kumar Chaurasia-- Head Sales, Glenmark
Rupam Kumar Chaurasia
Head Sales, Glenmark

Once I Joined DataTrained my learning curve started to grow steeply and as per the mentors I followed the new approach to get Data Science job.If I am successfully placed with one of the biggest data science firm complete credit lies with DataTrained and their competent Faculty.

Vanshika Rathi-- Data Analyst, Ola
Vanshika Rathi
Data Analyst, Ola

I did my research before deciding which course I should register myself for and of all the courses that I have found, the one offered by DataTrained was completely dedicated to analytics, after enrolling for Postgraduate Program for Data Science, I realized DataTrained Data Science course was ideal for me.

Surbhi Jain-- Sr. Data Specialist, Bank of America
Surbhi Jain
Sr. Data Specialist, Bank of America

Our Student Work At

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After my graduation, I didn't want to pursue MBA since everyone is doing it I wanted to do something different but I was confused. I opted for the PG Program in Data Science by Data Trained Education and I had an amazing journey with them, the trainers were top-notch, the course content was perfect.

Hemant Patar Placed at Maganti IT services--- DataTrained Placement
Hemant Patar
Maganti IT services

I can certainly say the content they are offering is really good. Assignments are relatable. Completing the assignments helps in a better understanding of the module. In a nutshell, I would recommend this course to anyone interested in Data Science.

Amandeep Placed at Analytics Vidya-- DataTrained Placement
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Analytics Vidya
Kumar Vaibhav Placed at HCL -- DataTrained Placement
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5 LPA
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Admission Process

There are 3 simple steps in the Admission Process that are detailed below

Step 1: Fill in a Query Form

Fill up the Query Form and one of our counselors will call you & understand your eligibility.

Step 2: Get Shortlisted & Receive a Call

Our Admissions Committee will review your profile. Upon qualifying, an Email will be sent to you confirming your admission to the Program.

Step 3: Block your Seat & Begin the Prep Course

Block your seat with a payment of INR 10,000 to enroll in the program. Begin with your Prep course and start your Data Analytics journey!

Program Fee

₹ 100000 + 18% GST

No Cost EMI options are also available. *

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Access to real-life projects

Access to domain specific mentorship

Access to career assist by IIMJobs

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