Job or refund
Job or refund

Data Science Training Course

Thane | Andheri | Online

Admission open : 27th September 2020

Weekdays & Weekend Batches

(Rated 4.8 based on 248 customer reviews)

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Why Data Science ?

Every company is generating data each day and they don’t know what to do with it and then they end up paying the highest salary to the person who has the knowledge of how to make maximum utilization of it. Tech companies seeing this data explosion in a huge manner are transforming their traditional IT skills into the new age of data analysis to reshape their businesses globally.

An international report stated that to manage this massive amount of data, the demand for Data Scientists is growing like anything and yet companies are only able to catch a few percentage of quality data scientists to explore the huge data locked in, eye-opening isn’t it? Now you know that Data is huge but not the Data Scientist that is why it is the most demanding job of the era.

In our Data Science certification course at Itvedant, we start with Python training – The most powerful of all programming languages. There are many programming languages used to handle the data like Python, R and C++ but amongst all Python is the most preferable language in the Industry due to its rich set of libraries, simple syntax & community-based approach.Further in data science class we study Statistics in order to understand the relation amongst your data i.e data modelling, then we shall refine the model created using Machine learning to give different algorithms which help to identify best model fit against the data pattern.Majorly when dealing with unstructured type data like images / audio we shall harness the power of Big data Analytics. When the outcome of certain metrics is unknown we let the machine learn by example so called Deep learning. Natural Language Processing , Computer Vision, Recommender Systems are applications of Machine Learning and Deep Learning. Artificial Intelligence is the final product outcome which will serve as a capstone project that is a usable product of all the technologies learnt and deployed on mobile / web.

What will you achieve from our Data Science Training Program

  • Collect and process large data using Big Data
  • Develop Image recognition application using CV
  • Develop Chatbot like application using NLP
  • Classify Customers using Machine Learning
  • Deploy your AI application
  • Use cases on real-world Data Science problems
  • Building Computer Vision Applications
  • Understanding of Time Series Analysis & Recommender system
Number of Freshers Enrolled
Freshers Enrolled
Number of active learners
Active Learners
Number of placed students
Already Placed
Number of tie up companies
Tie-up Companies

Data Science Training Key Features

Attend Interactive Training

From Any Location


Doubt Solving

Handson Training

Under Mentor

Only 7 Students

Per Batch

Naukri /Job Assurance


80% Practical,

20% Theory

Study App

Google Playstore

Certificate of


Data Science Course Modules

Python for Data Science

The extensive treasure of Data Science can be harnessed by various methods but Python is the most favoured and also most suitable due to its data structures and extensive modules like Numpy, Pandas or Scikit learn which we make a point to cover it in our Data Science Course. At Itvedant we don’t just teach Python to make you learn the syntax of a great programming language but teach you with different application development like Database Connectivity with MySQL and deployment using Flask Web Framework.

Statistics for Data Science

Statistics applies a mathematical model to a set of data. To formulate a mathematical model the basics of x and y and formulating the relation is taught in Linear Algebra. A practical approach to build a strong understanding of how to take a sample of data and apply it to the entire system in the machine learn is the base of inferential statistics. Trust us, learning these concepts will never be boring as college maths lecture as we try our best to relate it with a simple case of data science application.

Machine Learning for Data Science

Machine Learning is the basis of data science course and the most essential subject of data science. Machine Learning deals with teaching machine to learn just like how we teach our kids ! Kids or human learn from the surrounding by gathering data under a supervised environment of their parents / teacher ; relate it with supervised learing form of Machine Learning technique using algorithm such as regression and where we learn by observation is so called as Unsupervised learning – classification and clustering.

Big Data for Data Science

Data exists in structured form as well as unstructured form, for structured data we already dealt it with pandas in the Python for Data Science module while for largely unstructured data we shall primarily use Big Data.In Data Science course we will cover how to effectively use unstructured data that exists in images, text , web etc. The Big Data Analytics module in our data science course will deal about how do we deal with application of Machine Learning techniques on extremely large dataset modules.

TensorFlow & Keras

Google ® crafted a beautiful the TensorFlow library and released it to the Data Scientists to do complex tasks of Machine Learning and Deep Learning in Data Science in a simplistic way. Tensorflow provides an easy to use API in Python and calls itself end to end platform to deploy machine learning powered AI apps.After completion of this module you are also eligible for TensorFlow Certification to showcase your Machine Learning expertise.

Deep Learning – DL

When human learns by their own experience Data Science calls a machine learning by itself with the name ‘Deep Learning’. When you as a data scientist are performing tasks where the data is not labelled / classified and the outcome cannot be predfined we should use Deep Learning branch in Data Science. Deep Learning forms the foundation behind many concepts which we take ahead like – Natural Language Processing or Computer Vision. Deep Learning is also the underlying technology behind driverless car to recognise new objects.

Natural Language Processing – NLP

“Alexa ! what will be the temperature today at night 8 o’clock ?”. The demand for Artificial Intelligent apps like these which understands our language (not speech recognition) is huge in the field of Data Science where we make machines now learn deep using by processing our natural language – english just to start with. The grammar of the language, synonyms we use or the errors we make are part and parcel of this stream of Deep Learning / Machine Learning in our Data Science Course.

Computer Vision – CV

Computer Vision is recognition of objects such as cars, faces, fruits etc in an image. The simplest example of the application of computer vision using sophesticated Machine Learning algorithms in Data Science is the way your smartphone learns more and more about you using the face unlock technique (being fast to unlock). The world is full of imagination for what sorts of applications can be built if compter or machine learns from Image data.

Time Series Analysis

Analysing a periodic data to learn about the patterns in it is the Time Series Analysis branch of Machine Learning / Deep Learning in Data Science. The finance branch (commerce) has greatly witnessed the technology capabilities as the machines now accurately predict the stock prices or currency rates for the future. Using matplotlib and plotting x and y co-relation can easily help anyone understand the time based pattern of the system to be predicted using Machine Learning algorithms.

AI ⇌ Capstone Project

Artificial Intelligent apps are full and final product of multiple techniques which you have studies above. This requires a deployment platform to be studied like Web / Mobile / API for your Data Science Course outcome to be used by others. A personal guidance is required as every innovative project should be different than others. The Capstone project must involve aggregating learnings from multiple modules you just learnt in the Data Science Course. As an example we can build an app which can create a chatbot (using flask in python) to chat (natural language processing) using emojis (computer vision) to understand the mood / sentiments of the person over a week (time series analysis).

Career Opportunities in Data Science


  • Data Engineer – works on the data collection part, must be skilled enough to handle large amounts of data at scale. Must know programming in order to retrieve data from various sources and  cleaning up data sets.
  • Data Analyst – works on the EDA part, must have analytical skills, problem solving skills, knowledge of descriptive statistics and hands on experience on any visualization tool.
  • Data Scientist – works right from EDA to Model evaluation, must have good domain knowledge, analytical skills, knowledge of mathematical concepts like linear algebra, derivatives, geometry and vector algebra. Must have programming skills.
  • Machine Learning Engineer – responsible for deploying the final product to various platforms, must have basic knowledge of different platforms, virtual environments, programming and REST apis.

After gaining appropriate knowledge and skills, a fresher can always directly apply for the various job roles like Data Engineer, Data Analyst and Machine Learning engineer.

This is the first step, after gaining ample amount of experience in these roles, one can easily navigate their way towards the Data Scientist role. As mentioned earlier, a fresher with exceptional skills might get a direct Data Science job role, but again it depends on organization.

Apart from that, a fresher must also focus on other ways of getting into their dream jobs like –

  • Applying for internships.
  • Build a strong profile, showcase your work through Github.
  • Participate in Kaggle competitions.
  • Go to meetups, meet like minded people and build connections.

Be a Certified Data Scientist

Data science certificate

Data Science Master Certification

The Data Science master certification program prepares you for the heavy weight title – Data Scientist. Not just that along with the master certification of Data Science you shall be given 9 course module completion certificates at every check-point clearance if you are effective in meeting the Itvedant® Assessment Standards.And yes did we say you can easily clear the Google TensorFlow Exam with our guidance ? Look below

Tensorflow Certification

Itvedant prepares you for the Tensorflow Certification Program ! The Tensorflow Certification is recognised globally and your skills in Machine Learning is assessed by a company known by everyone ” Google® “.

google tensorflow certification itvedant

What Makes our Data Science program unique ?

  • We start with the basic fundamentals of programming and database technology so candidates can easily understand concepts.
  • Hands on classroom practices will be given.More than 150 basic to advanced level assignments will be given to solve.
  • Interactive classroom session.
  • 80% practical sessions 20% theoretical sessions.
  • Industry level case study will be given to solve.
  • Course and syllabus designed by industry experts.
  • 7+ to 10+ years experience faculty.
  • GitHub online repository for project development.
  • Linux OS based training.
  • Soft Skill development programs.

Our Alumni Works At

Max life
Reliance industries

Placed Students Offer Letter

Hear from the candidates themselves how is the experience of learning Data Science and Python – Machine Learning at Itvedant is like.

Gaurav experience at itvedant of learning python & Data science

“My name is Gaurav Chiplunkar due to having passion for coding & graphic designing I was looking for Software Programming Classes for Python in Thane, so one and half months back I join Itvedant. In Itvedant as far as I experienced teaching patterns is cool. They have good mentors who are professionally experienced under whom we students are taking guidance to step ahead into cooperate.”    -Gaurav Chiplunkar

Alumni Testimonials

Frequently Asked Questions

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