Data Science Training in Chennai

Deep learning with Python

Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. Deep learning is an aspect of artificial intelligence (AI) that is concerned with emulating the learning approach that human beings use to gain certain types of knowledge. At its simplest, deep learning can be thought of to automate predictive analytics. While traditional machine learning algorithms are linear, deep learning algorithms are stacked in a hierarchy of increasing complexity and abstraction.

How exactly Deep Learning helps us to classify?

Essentially Deep Learning involves feeding a computer system a lot of data, which it can use to make decisions about other data. This data is fed through neural networks, as is the case in machine learning. These networks – logical constructions which ask a series of binary true/false questions, or extract a numerical value, of every bit of data which pass through them, and classify it according to the answers received.

Some of real-world use case for Deep Learning.

• Object Classification in Photographs.
• Recoloring black and white images
• Predicting the outcome of legal proceedings
• Automated analysis and reporting

We offer Deep Learning course along with Python.

Syllabus

Deep Learning with PyTorch, Tensorflow and Keras

• Introduction to Neural Networks

• Implementing Gradient Descent
• Training Neural Networks
• Sentiment Analysis
• Deep Learning with PyTorch
• Convolutional Neural Network (CNN)
• CNNs in PyTorch
• Recurrent Neural Networks
• Long Short-Term Memory Network (LSTM)
• Sentiment Prediction RNN.

Data Science course in Chennai using R

Every case study gives you a chance to work on large, real-life business data sets in the advanced R lab.

• Programming with R
• Advanced R Features
• Using R Data Frames to solve complex tasks
• Use R to handle Excel Files
• Web scraping with R
• Connect R to SQL
• Use ggplot2 for data visualizations
• Use plotly for interactive visualizations
• Machine Learning with R, including:
• Linear Regression
• K Nearest Neighbors
• K Means Clustering
• Decision Trees
• Random Forests
• Data Mining Twitter
• Neural Nets and Deep Learning
• Support Vectore Machines
• and much, much more!

Enroll in the course and become a data scientist today!

Data Science training in Chennai with SAS

World-class Certified SAS Training Institute in Chennai for Base SAS, Advanced SAS, Clinical SAS, Analytics, Business Intelligence, Data Management, and Predictive Analytics

• Base SAS
• Advance SAS
• Clinical SAS Programming
• Predictive Modeling
• Clinical Data Manager
• Platform Administrator
• SAS Visual Analytics
• SAS Data Integration Studio
• BA Data Mining with Statistics
• Business Intelligence
• Data Management and Reporting

Data Science training course in Chennai with Python

Learn to use Python as your Data Science tool of choice This course teaches you Python as a tool for data science, and specifically for implementing an advanced Machine Learning algorithm with Python

I. Introduction and Setting Up Your Integrated Analysis Environment

Setting Up Your Integrated Analysis Environment & Tools Overview

• IPython Shell
• Custom environment settings
• Jupyter Notebooks
• Script editor
• Packages: NumPy, SciPy, scikit-learn, Pandas, Matplotlib, Seaborn, etc.

Once you complete this module, you will understand some of the unique benefits of using Python for data science / what features make Python particularly well-suited for data science, you will be able to set up a fully functioning Python-based analysis environment, and you will know what each tool is used for in the data science workflow.

II. Using Python to Control and Document Your Data Science Processes

Python Essentials

• Data types and objects
• Loading packages, namespaces
• Reading and writing data
• Simple plotting
• Control flow
• Debugging
• Code profiling

Once you complete this module, you will be able to use the Python standard library plus Canopy tools to write, run, debug, and profile programs that control your data science processes (which draw on the scientific packages).

III. Accessing and Preparing Data

Data, Data, Everywhere...

Acquiring Data with Python

• Loading from CSV files
• Accessing SQL databases

Cleansing Data with Python

• Stripping out extraneous information
• Normalizing data
• Formatting data

Once you complete this module, you will know how to load data from common types of data sources, including structured text files and SQL databases. and you will know some of the common tools used in Python to cleanse and prepare your data for analysis.

IV. Numerical Analysis, Data Exploration, and Data Visualization with NumPy Arrays,
Matplotlib, and Seaborn

NumPy Essentials

• The NumPy array
• N-dimensional array operations and manipulations
• Memory mapped files

Data Visualization

• 2D plotting with Matplotlib
• Advanced data visualization with Seaborn

Once you complete this module, you will understand how to use NumPy arrays for efficient numerical processing and how to use NumPy methods such as slicing to write code that is both compact and easy to read and understand. You will know how to use Matplotlib, Seaborn, and NumPy together to explore and visualize your data.

V. Exploring Data with Pandas

Searching for Gold in a Pile of Pyrite

• Data manipulation with Pandas
• Statistical analysis with Pandas
• Time series analysis with Pandas

At the end of this module, you will know how to access some of the core tools used for statistical analysis and data exploration in Python.

VI. Machine Learning with scikit-learn

Predicting the Future Can Be Good for Business

• Input: 2D, samples, and features
• Estimator, predictor, transformer interfaces
• Pre-processing data
• Regression
• Classification
• Model selection

At the end of this module you will have a working understanding of what machine learning tools are available in scikit-learn and how to use them.

Machine Learning for Data Science and Analytics

Learn the principles of machine learning and the importance of algorithms.

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI.

Data Science training in Chennai with Advanced SAS: Macros & SQL

Study advanced techniques in SAS - the most popular analytics language

Data Scientists, grab the opportunity to learn advanced data manipulation using SQL and Macros. Leap ahead in SAS by mastering the use of SQL as a data manipulation tool, the components of the SAS macro facility, the designing and debugging of macro systems, and more.

Oracle SQL Training Course Contents :

Introduction

• Describe the features of Oracle Database 12c
• Describe the salient features of Oracle Cloud 12c
• Explain the theoretical and physical aspects of a relational database
• Describe Oracle servers implementation of RDBMS and object relational database management system (ORDBMS)

1. Basic DATABASE Concept and SQL

• Basic history of database concept: DBMS, RDBMS, ORDBMS
• Advantage of ORACLE database and version information
• Interface tools usage: sqlplus, isqlplus, sqldeveloper, Toad
• SQL Language overview : DQL, DML, DDL, DCL, TCL
• What is the usage of ANSI standard.
• SELECT Command - Column Alias Rules, String data,
• Concatenations with various data
• Null Value handling with number and characters,
• Arithmetic Operator
• Concatenation Operator,
• Eliminating Duplicate Rows

2. Restricting and Sorting Data

• WHERE Clause - Character Strings and Dates, number
• General Comparison Conditions = > >= < <= <>
• Other Comparison BETWEEN , IN , LIKE , NULL
• Logical Conditions AND OR NOT
• ORDER BY Clause, Sorting by Column Alias , Column Position, Multiple Columns

3. Single-Row Functions

• Character Functions: UPPER, LOWER, INITCAP, LENGTH, SUBSTR, INSTR, LPAD, RPAD, CONCAT, LTRIM, RTRIM, TRIM, REPLACE, TRANSLATE, REVERSE
• Number Functions: ROUND, TRUNC, MOD, POWER, CEIL , FLOOR, ABS
• Dates Functions: SYSDATE, MONTHS_BETWEEN, NEXT_DAY, LAST_DAY, ADD_MONTHS, ROUND, TRUNC, Arithmetic on Date
• Conversion Functions: Implicit Data-Type Conversion & Explicit Data-Type Conversion, TO_CHAR ,TO_NUMBER ,TO_DATE
• General Functions: NVL , NVL2 , NULLIF, COALESCE
• CASE Expression, DECODE
• Nested function with real-time usage

4. JOINS

• EQUI JOIN / SIMPLE JOIN / NORMAL JOIN
• ANSI JOIN, LEFT OUTER, RIGHT OUTER, FULL OUTER
• NATURAL JOIN, NATURAL OUTER JOINS
• INNER JOIN, JOIN ... USING clause, JOIN ... ON clause,
• CROSS JOIN, NON-EQUI JOIN, SELF JOIN
• ORACLE STANDARD OUTER JOINS.
• Multi table Joins, Complex Joins How to simplified complex joins.

5. Multi-row Functions

• Group Functions Rules, SUM, MIN, MAX, COUNT, AVG
• Creating Groups of Data: GROUP BY Clause
• Filtering Group Results: The HAVING Clause

6. Sub-queries

• Single-Row Subqueries- Rules, Operators : = > >= < <= <>
• Null Values in a Subquery
• Multi-Row Subqueries- Rules, Operators : IN, ANY , ALL

7. Reporting data using interface commands

• pagesize, linesize , column heading , column format , colsep
• tTitle , bTitle , break on column, spool , CSV file generation, Text file generation

8. Data Manipulation Language DML and Transaction Control Language TCL

• DML : INSERT, UPDATE, DELETE, MERGE
• TCL : COMMIT, ROLLBACK, SAVEPOINT

9. Data Definition Language - DDL

• DDL : CREATE, ALTER, RENAME, DROP, TRUNCATE
• DEFAULT OPTION.
• Constrain table copy

10. Constraints

• NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK
• Column Level Constraint, Table Level Constraint Naming constraints and usage
• Adding a Constraint, Dropping a Constraint,
• Disabling Constraints, Enabling Constraints
• Validating Constraints

11. Views

• Simple Views and Complex Views , Create, Drop, Source Code
• Rules for Performing DML Operations on a View
• WITH CHECK OPTION , WITH READ ONLY
• Inline Views
• Materialized View , Create, Refresh, Drop - Usage

12. Other Database Objects

• Sequence- NEXTVAL and CURRVAL
• Index - When to Create an Index, When Not to Create an Index.
• Synonyms

13. DCL COMMANDS

• Creating Users
• Granting / Revoking Privileges
• Creating and Granting Privileges to a Role

14. Dictionary Tables

• Tables, Views, Synonyms, Index, Sequence, Constrains, Source and other Dictionary

15. SET Operators

• UNION ,
• UNION ALL ,
• INTERSECT ,
• MINUS

16. Advanced Date-time Functions

• TIME ZONES ,
• SYSDATE, SYSTIMESTAMP,
• CURRENT_DATE , CURRENT_TIMESTAMP
• SESSIONTIMEZONE ,
• Storing time zone data in Table
• EXTRACT ,
• TO_YMINTERVAL

17. Advanced GROUP BY Clause

• Group by with ROLLUP,
• Group by with CUBE,
• GROUPING SETS

18. Advanced Subqueries

• Pairwise Comparison Subquery ,
• Nonpairwise Comparison Subquery
• Correlated Subqueries,
• Correlated UPDATE,
• Correlated DELETE
• EXISTS , NOT EXISTS Operator

19. Hierarchical Retrieval

• Walking the Tree: From the Bottom Up , From the Top Down
• LEVEL Pseudo column,
• Connect by prior,

20. Multi-table Insert

• Unconditional INSERT ALL
• Conditional INSERT ALL
• Conditional FIRST INSERT

21. DATA LOADER

• SQLLDR Loading CSV file / Flat file into ORACLE table.

22. Analytic Functions

• WM_CONCAT, LAG, LEAD, RANK, DENSE_RANK
• Query_by partition_clause with sum, min, max, avg, count,
• order_by_clause with sum, min, max, avg, count,
• Psudo column : Rownum, Rowid, - Elimination duplicate data
• Connect by rownum , Connect by Level Generating random numbers, random dates,
• Quote Operator syntax and usage

23. Backup

• Export / Import SCHEMA

24. General discussion

• What is migration?
• Migration Estimating, Planning, Preparation Simple Scenario / Complex Scenario.

Data Science training in Chennai with Excel Macro

Creating Record Macros

1. Recording a Macro
2. Running a Macro
3. Running a Macro from the Macros Dialog Box
4. Creating a Short-cut key to run a macro
5. Running a Macro with a Shortcut key
6. Assigning a Macro to a Menu or Toolbar
7. Editing a Macro with Visual Basic

Visual Basic Editor

1. Objects
2. Methods
3. Properties
4. Programming Tools
5. The Menu Bar

The Project Explorer

1. Using the Project Explorer

Using Constants

1. Excel Constants
2. Variable Constants

Excel Objects

1. Objects, Properties and Methods
2. Getting & Setting Properties
3. Calling Methods
4. Passing Arguments
5. Singular Objects & Collections of Objects

Using Visual Basic Functions

1. InputBox Function
2. MsgBox Function
3. Using a Set Statement

Building Formular Control Structures

1. If Then Janision Structures
2. Logical Operators
3. Select Case Janision Structures
4. Case Else
5. Comparison Operators with Select Case Structure
6. For Loops
7. Do Loops
8. While...Wend Statement

Running Code

1. Run mode and Design mode
2. Running Code from the development environment
3. Running Code from the host application

The Properties Window

1. Changing a Property

Variables

1. Dimensioning a variable
2. Using variables in routines
3. Object Variables

UserForms

1. Designing & Creating Forms
2. Working with Controls
3. Creating Custom Dialog Boxes
4. Userform Properties Methods & Events

Advanced VBA Programming Techniques

1. Developing Excel Utilities with VBA
2. Error Handling
3. Using In-Built Excel Features in VBA
4. Working with Pivot Tables
5. Working with Charts
6. Understanding Excel's Events
7. Interacting with Other Applications
8. Creating and Using Add-Ins

Developing Applications

1. Working with the Ribbon
2. Working with Shortcut Menus
3. Providing Help for Your Applications
4. Developing User Oriented Applications

Event Handling

1. VBA Editing & Debugging
2. Auto Macros
3. Error Handling

Connecting to Database

1. Connect to MS Access
2. Access Database & Retrieve Data from MS Access
3. Create Table & Query Data Filter DB using Query
4. Update and Modify DB
5. Create Single and Multiple Mapping Tables
6. Filter DB using Query
7. Query data grouping
8. Retrieve Data using Logical Access Query

Connect Excel to Outlook

1. Connect to Outlook using VBA
2. Query to retrieve Mail From, to and CC address
3. Retrieve Mail Subject and Time
4. Retrieve Mail Attachment

Best Data Science Training in Chennai

" I am glad to have taken complete Data Science course in Greens Technologys. It helped me a lot in understanding various concepts before which I was depending on many other sources. I will recommend this course to beginners as well as experienced Data Science Developers to attend the courses offered by Radha Krishnan @ Greens Technologies Adyar. The course curriculum is meticulously prepared and also followed without any compromise. Thus, the beginners can understand how to begin learning a vast technology without any confusion. In my case, attending this course, helped me firstly how to learn the subject in a different approach (understandings basics level to in depth concepts), instead of rushing through various text books or online sources. Dinesh explains every concept in a very interesting way and it always creates an excitement in learning more about Java. Moreover the material, notes from training also helps us prepare for interviews, Data Science real time projects as well.

Best Data Science Training institute in Chennai

"I did my Android and Data Science training in greens technology, Chennai. Now I got placed in Virtusa. I really thank Muthu for his involvement in my training. His way of teaching is really awesome. I never saw such quality teaching and placements were so fast. Thanks a lot Greens Technologys for your support. I wish Muthu sir all the best for his new IT development venture

Best Data Science Training & Placement in Chennai

"Thank you for the immediate placement after the completion of Data Science course from Greens Technology. The trainer Muthu sir (12 yrs exp) here are Real time working expert and have excellent knowledge on their subject .They guided me to get thru the interview process. Best thing is that they stay in touch with the students even after the placement and help us growing.I am very happy to write testimonial for Greens Technology. Dinesh sir is like my big brother"

Data Science Training & Placement Institute in Chennai

"My greetings to Data Science God Karthik of Greens temple.As a Data Science Pilgrim i have gained power of Data Science.I know what iam before entering to this holy place and now i know i have acquired magic power of Data Science. With your blessings iam going to enter in to programming world.I wish there was some way of showing my gratitude for all what you have done for me....Loving You...... UrsForever"

Data Science certifications Training in Chennai

• Analytics: Optimizing Big Data Certificate
• Certificate in Engineering Excellence Big Data Analytics and Optimization (CPEE)
• Certification of Professional Achievement in Data Sciences
• Certified Analytics Professional
• EMC Proven Professional Data Scientist Associate (EMCDSA)
• IBM Certified Data Architect – Big Data
• IBM Certified Data Engineer – Big Data
• Microsoft Certified Solutions Expert (MCSE): Data Management and Analytics
• Mining Massive Data Sets Graduate Certificate
• MongoDB Certified DBA Associate
• MongoDB Certified Developer Associate
• Oracle Business Intelligence Foundation Suite 11 Certified Implementation Specialist
• SAS Certified Big Data Professional
• SAS Certified Data Scientist Using SAS 9
• Cloudera Certified Associate (CCA) Administrator
• Cloudera Certified Associate (CCA) Data Analyst
• Cloudera Certified Associate (CCA) Spark and Hadoop Developer
• Cloudera Certified Professional (CCP): Data Engineer
• Stanford Data Mining and Applications Graduate Certificate

Data Science Training in Chennai Benefits

• My batch sizes are generally very small size 5-7 members OR 1 to 1 also, so students receive direct, hands-on training from us.
• 100% practical training only. It is not a slide show training program / theory class program. At the end of this class, definitely you will refer your colleagues / friends / relatives for my training.
• Conducting regularly online- training for US peoples in all time zones (PST,CST,EST,HST,MST)
• Installation of Softwares in your desktop / laptop will be done.
• Will be provided self evaluation testing software, exam simulator, dumps & books with this training.
• Continuous support is provided for any of your on-site problems. assistance will be provided and you will be recommended to some of IT development firms.

Data Science Corporate Training in Chennai

Private Bootcamps

You have a team that already understands your company. We’ll enhance their skills and transform them into being able to extract actionable insights from your company’s data.

• Hosted at a location convenient to you
• Caters to a large group of employees from the same organization
• Inlcudes our popular five-day curriculum

Data Science Online Training in Chennai

Conducting regularly online- training for US peoples in all time zones (PST,CST,EST,HST,MST) My training is 100% Money Back Guarantee (Tuition fee) for Passing Online Examination with cent percent and ready to go live with production system immediately. If my training does not satisfy you at any point of time, even during the training period, you need not pay the tuition fee.
100% practical training only. It is not a slide show training program / theory class program. At the end of this class, definitely you will refer your colleagues / friends / relatives for my training.