How to become a Data Scientist & get placed ?

Any fresher and candidates up to 3 years work-ex
can become Data Scientist
by pursuing

Masters in Data Science Programme

    Course Highlights:

  •  250 hrs of hands-on Live-online-class training. Spread over a period of 6 months

  •  Split into six modules, namely SQL for Databases, Data Analytics for Business, Statistics using Excel & Tableau, Python Programming, Machine Learning, Advanced Machine learning with Capstone Projects

  •  100% placement calls

  •  Course is designed to give maximum choice and time flexibility to working professionals

  •  Weekday & Weekend batches on Google classroom

  •  More than 3000+ reviews about training@Suven on social media

  •  Only Online-Live-Classroom coaching with 200% ROI

  • Total Fee : INR 51000 45000/-

     Also get additional ML-Intermidate worth Rs6000/- free

Success Stories

78% placement ratio averaged over last 10 years

3000+ students trained and placed in last 5 years

Have got 4.6 stars on Google reviews

SQL the first skill to learn under
this course
"Masters in Data Science"

Oracle SQL training and Exam Prep Module

What is SQL?
SQL (Structured Query Language) is the primary language responsible for managing data held in a relational database management system (RDBMS). Simply put, SQL is the language you use to interact with a database.

Who should learn SQL ?
Product Managers, Data Analysts, Data Scientists, Data Engineers,
Backend Developers, Frontend developers, Mobile App Developers, Marketers

    Course Highlights:

  •  24 hrs of Hands-on training on oracle-11g/12c/18c/19c

  •  Many e-books : Theory, Practical Try-outs, 7 Oracle SQL Mock test papers

  •  Complete software support on

  •  100% Oracle SQL Exam clearance guarantee

  •  One online mock test exactly on lines of Oracle/hackerrank 3 to 5 stars

  • Fee (only for) Oracle SQL Training : INR 5000/-


    For Syllabus visit

    Register here for getting batch updates

    Batch time table for all subjects - here


    1) Oracle Database Express Edition 12c Download Or use live SQL

    2) Oracle Database Express Edition 11g Download Or use live SQL

    3) Installation Steps - Oracle DB 10g/11g - By Rocky Sir Download

    4) How to run java-database programs from my PC ? Download

    5) Solution (by Rocky Sir) to HackerRank > SQL problems Download    ReadMe.txt

    6) Foreign Key Constraint Example -- important !! Must See Once

    7) Learn Oracle SQL : The Hierarchical Query Clause Must See Once

    8) Top-N queries in Oracle SQL Must See Once

    9) Understanding Analytic Functions in Oracle SQL Must See Once

    10) Overview of Regular Expressions in Oracle 11g Must See Once

    For many more downloads please visit

Data Analysis is the second skill to learn under
this course
"Masters in Data Science"

Data Analytics using R / Python

What Makes Programming Languages Like Python or R a Good Choice ?
1) Python as well as R are two open-source programming languages.
2) Best used for performing statistics, analysis and visualization.
3) It as The Ultimate Statistical Analysis Kit.

    Course Highlights:

  •  40 hrs of hands-on training on week-ends

  •  One month of internship on semi-live datasets

  •  Participate in Kaggle Data Analytics competition, with the subject trainer as mentor.

  •  Post the course a participant can easily analyze real-time datasets and crack interviews for junior data Analyst positions.

  • Fee (only for) this module : INR 8000/-


    Download course contents here

    Register here for getting batch updates

    Batch time table for all subjects - here

Downloads for DA using Python:

  1. Want to learn Basics of Python-Quickly - Jupyter notebook download
  2. Introduction_Recalling_List,_dictionary_and_Regex - Jupyter notebook download
  3. NumPy: Python's Vectorization Solution - Jupyter notebook download
  4. Data Analysis With Pandas - Jupyter notebook download
  5. Matplotlib - Jupyter notebook download
  6. Exploratory Data Analysis - Jupyter notebook download
  1. Datasets used in the course work - download
  2. Images used in the Notebooks - download
  3. Workspace for DA using Python -

Statistics is the third skill to learn under
this course
"Masters in Data Science"

Statistics using Excel and Tableau

Statistics is the science concerned with developing and studying methods for collecting, analyzing, interpreting and presenting empirical data.

For example, data analysis requires descriptive statistics and probability theory, at a minimum. These concepts will help you make better business decisions from data.

Key concepts include probability distributions, statistical significance, hypothesis testing, and regression.

    Course Highlights:

  •  Complete know-how of Statistical concepts with applications.

  •  Implementation of Statistical concepts through Excel

  •  Data visualization through Tableau

  •  Two Excel-data Analysis projects to be submitted as part of the term-work for course completion

  •  Any participant post this course module can easily understand real-time data.

  • Fee (only for) Statistics : INR 6000/-

Python Programming is the fourth skill to learn under
this course
"Masters in Data Science"

Python Programming (Core + Advanced)

Python is a general purpose programming language. Created nearly 30 years ago, it is now one of the most popular language according to the Stackoverflow rankings. Its popularity is particularly important in the data science and machine learning fields. But it is also a language easy to learn, this explains why it has become the language the most taught in universities.

What is python used for ?

  1. Web Development, using the frameworks Django, Flask, Pylons
  2. Data Science and Visualization using Numpy, Pandas and Matplotlib
  3. Machine learning with Tensorflow and Scikit-learn
  4. Desktop applications with PyQt, Gtk, wxWidgets and many more
  5. Mobile applications using Kivy or BeeWare
  6. Education: Python is a great language to learn programming!

    Course Highlights:

  •  17 sessions of 3 hrs each covering 3 major sections of generic python programming namely Core, Routine Business Task automation, Advanced.

  •  The course does not* focus on "Python for Data Science", as this makes the learner in-competent for many interviews. (*Python for Data Science is covered under "Machine Learning course" module)

  •  Each participant can do a 2 weeks of Online Internship on problem statements submitted by IT professionals working at Morgan Stanley, Accenture and NeoSoft.

  • Fee (only for Python) : INR 9000/-


    Download course contents here

    Register here for getting batch updates

    Batch time table for all subjects - here

Downloads: work-space - download work-space - download work-space - download

    Complete work-space for 17 chapters with needed resources

    Project Specifications
  1. Combine select pages from many pdfs - download

  2. Web Scrapping - Find email address and phone numbers from a web page - download

Machine Learning is the fifth skill to learn under
this course
"Masters in Data Science"

Machine Learning

Machine Learning is an application of Artificial Intelligence. It allows software applications to become accurate in predicting outcomes. It helps in making data-driven decisions at scale for businesses.

Getting key information or insights from data is the key reason; businesses and organizations invest heavily in a good workforce as well as newer paradigms and domains like Machine Learning.

Machine Learning is heavily being used in Healthcare, Finance, Real Estate and Electronics (specifically Personal Device Market).

    Course Highlights:

  •  40 hrs of hands-on training covering all concepts & algorithms in ML

  •  Covering Python for Data Science - Numpy, Pandas, Matplotlib and Scikit Solving simple case studies

  •  Being ready for "Advanced Machine learning" course

  • Fee (Only for Machine Learning) : INR 8000/-


    Download course contents here

    Register here for getting batch updates

    Batch time table for all subjects - here


  1. Setup python machine learning packages - download

  2. Python Data types used in ML programming (a small refresher) - download

  3. Complete Machine Learning eNotes - download

  4. CaseStudy_1_ml_Predicting Student Grant Recommendations - download

  5. NumPy basics - Jupyter notebook download

  6. Pandas for data Analysis - Jupyter notebook download

  7. Matplotlib for Data Visualization - Jupyter notebook download

  8. Scikit-Learn for Data Science - Jupyter notebook download

  9. Datasets and Images needed for above Jupyter notebooks - download

  10. Complete workspace - of all Jupyter Notebooks -

Advance Machine Learning is the last skill to learn for
completing this course
"Masters in Data Science"

Advance Machine Learning

After completing the fundamentals of Machine learning in the previous course, this course would take you deeper and boarder into Machine learning.

This course module is designed to teach through projects focusing on
NLP (Natural Language processing), Text processing, Text classification, Text analytics and Sentiment Analysis. Machine learning and Deep learning(RNN & LSTM) algorithms are well understood and applied through out the course.

    Course Highlights:

  •  Overall coverage of NLP Libraries and understanding its key applications.

  •  Solve 4 real time case studies using raw (unclean) data.

  •  Understanding RNN & LSTM and solving four types of NLP problems.

  •  Clear understanding of all Types of Neural Networks and its applications.

  •  Performing Text Analytics and Sentiment analysis on real time data.

  •  Working on at-least one Capstone project with real datasets.

  •  *Participating in Kaggle competitions under the mentor-ship of the subject trainer.

  • Fee (Only for Advance Machine Learning) : INR 15000/-


    Download course contents here

    Register here for getting batch updates

    Batch time table for all subjects - here


  1. Use Google Colab here

  2. Complete Advance Machine Learning eNotes - download

  3. work-space for Part 2 - Jupyter Notebook - download

  4. work-space for Part 3 - Jupyter Notebook

  5. work-space for Part 4 - Jupyter Notebook

  6. work-space for Part 5 - Jupyter Notebook

  7. work-space for Part 6 - Jupyter Notebook

  8. work-space for Part 7 - Jupyter Notebook

  9. Data-sets and Images - download

  10. Are you ready to face Interviews ? - Check here