Best Training institute in gurgaon
Best Training institute in gurgaon

578/2, New Railway Road, Near OBC Bank, Gurgaon

M-12, 1st Floor OLD DLF Colony, Sec-14, Gurgaon

Best Complete Data Scientist Training in Gurgaon

Best Complete Data Scientist Course in Gurgaon | Best Data Scientist Training Institute in Gurgaon|Best Data Scientist Training in Gurgaon

Get the best Complete data training in Gurgaon. TCA is popular for providing quality training and education in Gurgaon and we can proudly say that TCA is one of the top Complete data training providers in Gurgaon. Our all Complete data trainers are experts in the training industry. The Complete data training we provide is designed to suit the industry standard curriculum which makes it a 100% Job Guaranteed training program offered by us.

We at TCA, provide training which is live projects based training on Complete data which creates confidence in students. Complete data training in TCA is all about practical knowledge and hands-on experience. Here we teach students to learn, develop as well as deploy their Complete data projects with us. Our industrial training on Complete data program is guaranteed with 100% job assurance. Students having Complete data certification from TCA are able to secure jobs in MNC.

All our trainers are very experienced in their respective field. All our trainers are professional and have plenty of experience and practical knowledge which they love to share with the students. Our expert trainers will guide you throughout the training to make you get ready for your dream job.

We take full responsibility for the training of the student. We train the students from the basic level to advanced concepts with a real-time environment. By joining the best Complete data training provider in Gurgaon you will get the hands-on practice and thorough knowledge of subjects. This will increase their experience and built confidence in them.

A student who joins TCA, best Complete data institute in Gurgaon becomes a family of member TCA. After the completion of the Complete data training/course and certification. They get Complete data training with the placement solution. In this placement solution, our placement team schedule placement drives and also send students to MNCs for interviews through our references. So, the assurance of job and moderate training fee support students to achieve their goals.

Under our industrial training on Complete data program, we train students to develop 2 Projects during the period of 6 months industrial training on Complete data. We help students to experience the real feel of industry's working environment during Complete data training in Gurgaon. During their 6 months, industrial training period they come to learn the complete phases of SDLC.

In the best Data Scientist training in Gurgaon TCA provide the Data Scientist training and certification along with the placement program. The main topics which are going to be covered in Data Scientist training are Introduction to Business Analytics, R Programming, Predictive modeling in R, Tableau, Data Analyst using SQL, Data science using Python, Data Science & Machine Learning in Python, and many more.

Complete data Training in Gurgaon Course Content/Syllabus
Here is our Complete data course syllabus given to understand the entire topics which will be covered in Complete data. We recommend you to first go through this Complete data syllabus properly which will enable to understood the things easily.

Check our other programs

Along with this course we have expert faculties who provide a lot of different other courses such as C and C++ Programming, Java (core) and Advance Java with frameworks, Android, Web Designing, PHP, Microsoft .NET, Big Data Hadoop, etc in CS/IT department and courses like AutoCAD, Solid Works, Primavera, Ansys, Revit, etc in Civil/Mechanical department and in Skill Development there courses such as Advance Excel, Microsoft Office, Tally ERP, Stenography Typing, etc. For more information, you can visit pages and know more or you can contact us.

Data Scientist Training

Data Scientist Course Content

Introduction to Business Analytics

  • What is analytics & why is it so important?
  • Applications of analytics
  • Different kinds of analytics
  • Various analytics tools
  • Analytics project methodology
  • Real world case study

R Programming

Fundamentals of R

  • Installation of R & R Studio
  • Getting started with R
  • Basic & advanced data types in R
  • Variable operators in R
  • Working with R data frames
  • Reading and writing data files to R
  • R functions and loops
  • Special utility functions
  • Merging and sorting data
  • Case study on data management using R
  • Practice assignment

Data visualization in R

  • Need for data visualization
  • Components of data visualization
  • Utility and limitations
  • Introduction to grammar of graphics
  • Using the ggplot2 package in R to create visualizations

Data preparation and cleaning using R

  • Needs & methods of data preparation
  • Handling missing values
  • Outlier treatment
  • Transforming variables
  • Derived variables
  • Binning data
  • Modifying data with Base R
  • Data processing with dplyr package

Understanding the data using univariate statistics in R

  • Summarizing data, measures of central tendency
  • Measures of variability, distributions
  • Using R to summarize data
  • Case study on univariate statistics using R
  • Practice Assignment

Hypothesis testing and ANOVA in R to guide decision making

  • Introducing statistical inference
  • Estimators and confidence intervals
  • Central Limit theorem
  • Parametric and non-parametric statistical tests
  • Analysis of variance (ANOVA)
  • Conducting statistical tests
  • Practice Assignment
Predictive modeling in R

Correlation and Linear regression

  • Correlation
  • Simple linear regression
  • Multiple linear regression
  • Model diagnostics and validation
  • Case study

Logistic regression

  • Moving from linear to logistic
  • Model assumptions and Odds ratio
  • Model assessment and gains table
  • ROC curve and KS statistic
  • Case Study

Techniques of customer segmentation

  • Need for segmentation
  • Criterion of segmentation
  • Types of distances
  • Clustering algorithms
  • o Hierarchical clustering
  • o K-means clustering
  • Deciding number of clusters
  • Case study

Time series forecasting techniques

  • Need for forecasting
  • What are time series?
  • Smoothing techniques
  • Time series models

Decision trees

  • What are decision trees
  • Entropy and Gini impurity index
  • Decision tree algorithms
  • Case Study


Introduction and Overview

  • Why Tableau? Why Visualization?
  • TableauLevel Setting – Terminology
  • TableauGetting Started – creating some powerful visualizations quickly
  • TableauThe Tableau Product Line
  • TableauThings you should know about Tableau

Getting Started

  • Connecting to Data and introduction to data source concept
  • TableauWorking with data files versus database server
  • TableauUnderstanding the Tableau workspace
  • TableauDimensions and Measures
  • TableauUsing Show Me!
  • TableauTour of Shelves (How shelves and marks work)
  • TableauBuilding Basic Views
  • TableauHelp Menu and Samples
  • TableauSaving and sharing your work


  • Creating View
  • TableauMarks
  • TableauSize and Transparency
  • TableauHighlighting
  • TableauWorking with Dates
  • TableauDate aggregations and date parts
  • TableauDiscrete versus Continuous
  • TableauDual Axis / Multiple Measures
  • TableauCombo Charts with different mark types
  • TableauGeographic Map Page Trails
  • TableauHeat Map
  • TableauDensity Chart
  • TableauScatter Plots
  • TableauPie Charts and Bar Charts
  • TableauSmall Multiples
  • TableauWorking with aggregate versus disaggregate data
  • Analyzing
  • TableauSorting & Grouping
  • TableauAliases
  • TableauFiltering and Quick Filters
  • TableauCross-Tabs (Pivot Tables)
  • TableauTotals and Subtotals Drilling and Drill Through
  • TableauAggregation and Disaggregation
  • TableauPercent of Total
  • TableauWorking with Statistics and Trend lines

Getting Started with Calculated Fields

  • Working with String Functions
  • TableauBasic Arithmetic Calculations
  • TableauDate Math
  • TableauWorking with Totals
  • TableauCustom Aggregations
  • TableauLogic Statements


  • Options in Formatting your Visualization
  • TableauWorking with Labels and Annotations
  • TableauEffective Use of Titles and Captions
  • TableauIntroduction to Visual Best Practices

Building Interactive Dashboard

  • Combining multiple visualizations into a dashboard
  • TableauMaking your worksheet interactive by using actions and filters
  • TableauAn Introduction to Best Practices in Visualization

Data Analyst using SQL

Introduction to SQL

  • What is SQL
  • Why SQL
  • What are relational databases?
  • SQL command group
  • MS SQL Server installation
  • Exercises

SQL Data Types & Operators

  • SQL Data Types
  • Filtering Data
  • Arithmetic Operators
  • Comparison operators
  • Logical Operators

Useful Operations in SQL

  • Distinct Operation
  • Top N Operation
  • Sorting results
  • Combine results using Union
  • Null comparison
  • Alias

Aggregating Data in SQL

  • Aggregate functions
  • Group By clause
  • Having clause
  • Over clause

Writing Sub-Queries in SQL

  • What are sub-queries?
  • Sub-query rules
  • Writing sub-queries

Common function in SQL

  • Ranking functions
  • Date & time functions
  • Logical functions
  • String functions
  • Conversion functions
  • Mathematical functions

Analytic Functions in SQL

  • What are analytic functions?
  • Various analytic functions
  • SQL syntax for analytic functions

Writing DML Statements

  • What are DML Statements?
  • Insert statement
  • Update statement
  • Delete statement

Writing DDL Statements

  • What are DDL Statements?
  • Create statement
  • Alter statement
  • Drop statement

Using Constraints in SQL

  • What are constraints?
  • Not Null Constraint
  • Unique constraint
  • Primary key constraint
  • Foreign key constraint
  • Check constraint
  • Default Constraint

SQL Joins

  • What are joins?
  • Cartesian Join
  • Inner Join
  • Left & Right Join
  • Full Join
  • Self Join

Views in SQL

  • What are views?
  • Create View
  • Drop view
  • Update view

Data science using Python

Introduction to Data Science

Python Training

  • Introduction to Python
  • Installation of Python framework and packages: Anaconda and pip
  • Writing/Running python programs using Spyder, Command Prompt
  • Working with Jupyter Notebooks
  • Creating Python variables: Numeric, string and logical operations
  • Basic Data containers: Lists, Dictionaries, Tuples & sets
  • Practice Assignment

Iterative Operations & Functions in Python

  • Writing for loops in Python
  • List & Dictionary Comprehension
  • While loops and conditional blocks
  • List/Dictionary comprehensions with loops
  • Writing your own functions in Python
  • Writing your own classes and functions as class objects
  • Practice assignment

Data Summary; Numerical and Visual in Python

  • Need for data summary
  • Summarising numeric data in pandas
  • Summarising categorical data
  • Group wise summary of mixed data
  • Need for visual summary
  • Introduction to ggplot & Seaborn
  • Visual summary of different data combinations

Data Handling in Python using NumPy & Pandas

  • Introduction to NumPy arrays, functions &properties
  • Introduction to pandas
  • Dataframe functions and properties
  • Reading and writing external data
  • Manipulating Data Columns

Data Science & Machine Learning in Python

Introduction to Machine Learning

  • Business Problems to Data Problems
  • Broad Categories of Business Problems
  • Supervised and Unsupervised Machine Learning Algorithm
  • Drivers of ML algos
  • Cost Functions
  • Brief introduction to Gradient Descent
  • Importance of Model Validation
  • Methods of Model Validation
  • Introduction to Cross Validation and Average Error

Generalised Linear Models in Python

  • Limitation of simple linear models and need of regularisation
  • Ridge and Lasso Regression (L1 & L2 Penalties)
  • Introduction to Classification with Logistic Regression
  • Methods of threshold determination and performance measures for classification score models
  • Case Studies

Tree Models using Python

  • Introduction to decision trees
  • Tuning tree size with cross validation
  • Introduction to bagging algorithm
  • Random Forests
  • Grid search and randomized grid search
  • ExtraTrees (Extremely Randomised Trees)
  • Partial Dependence Plots

Boosting Algorithms using Python

  • Concept of weak learners
  • Introduction to boosting algorithms
  • Adaptive Boosting
  • Extreme Gradient Boosting (XGBoost)

Support Vector Machines (SVM) and KNN in Python

  • Introduction to idea of observation based learning
  • Distances and Similarities
  • K Nearest Neighbours (KNN) for classification
  • Introduction to SVM for classification
  • Regression with KNN and SVM

Unsupervised learning in Python

  • Need for dimensionality reduction
  • Introduction to Principal Component Analysis (PCA)
  • Difference between PCAs and Latent Factors
  • Introduction to Factor Analysis
  • Patterns in the data in absence of a target
  • Segmentation with Hierarchical Clustering and K-means
  • Measure of goodness of clusters
  • Limitations of K-means
  • Introduction to density based clustering (DBSCAN)

Neural Networks

  • Introduction to Neural Networks
  • Single layer neural network
  • Multiple layer Neural network
  • Back propagation Algorithm
  • Neural Networks implementation in Python

Text Mining in Python

  • Quick Recap of string data functions
  • Gathering text data using web scraping with urllib
  • Processing raw web data with BeautifulSoup
  • Interacting with Google search using urllib with custom user agent
  • Collecting twitter data with Twitter API
  • Introduction to Naive Bayes
  • Feature Engineering for text Data
  • Feature creation with TFIDF for text data

Ensemble Methods in Machine Learning

  • Making use of multiple ML models taken together
  • Simple Majority vote and weighted majority vote
  • Blending
  • Stacking

Version Control using Git and Interactive Data Products

  • Need and Importance of Version Control
  • Setting up git and github accounts on local machine
  • Creating and uploading GitHub Repos
  • Push and pull requests with GitHub App
  • Merging and forking projects
  • Introduction to Bokeh charts and plotting

Why Choose TCA for Data Scientist Training in Gurgaon

  • TCA has highly experienced and qualified professional trainers.
  • Learn Data Scientist with hands-on practice in a real environment.
  • TCA's best Data Scientist training in Gurgaon provides job oriented course's syllabus.
  • TCA provides Live project-based Data Scientist training in Gurgaon.
  • TCA's Data Scientist training in Gurgaon is designed to suit the industry standard curriculum.
  • Authorized Data Scientist Certification.
  • Fast Track classes are also available with best course fees.
  • TCA training institute in Gurgaon provide well-equipped lab facilities and decent infrastructure for Data Scientist training.
  • Our best placement solution for job assurance.
  • TCA's Data Scientist training center in Gurgaon provide Data Scientist training in weekdays as well weekends.
  • At TCA, the best training company in Gurgaon we facilitate students with updated modern I.T technology and best learning environment.
  • We provide our own books editions which are designed to make the learning more easy and efficient.
  • Our labs have big screens and projectors which makes learning quite interesting.

TCA's Trainer's Profile for Data Scientist Training in Gurgaon

  • Our trainers are experts in Data Scientist technology.
  • Our trainers are highly experienced and mastered the Data Scientist technology.
  • Our trainers know the demands of today's industry so they provide the training considering the industry competitions.
  • Our trainers have different important post working as an employee in Bank of America,
  • Our trainers have long teaching experience so they teach the students according to their level.

Placement Assistance

Job-Oriented Sessions
  • Employability Orientation Sessions
  • Grooming Sessions & Technical Seminar
  • Interview Trick & Tips by Experts
  • Resume Writing Sessions
  • Session on
  • Personality Development Sessions
  • Group Discussion Sessions
  • Week-End Seminars

Live Video Sessions

Attend Video Classes
  • Online Classes Available
  • Recorded Sessions Demo Download
  • Lesson on Demand Available
  • Live Streaming of Selective Sessions
  • You can schedule your class online
  • Special Videos from Experts
  • Check Classes Live Schedule
  • Book your online Demo

Our Membership

One Year Membership
  • One Year membership card
  • Revision Sessions for one year
  • You can come on Week-ends
  • Special Sessions Notifications
  • All workshop free for one year
  • Practice anytime on any day
  • Trainers connect for one year
  • Online Content Access for one year