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BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Select BY Variables Updating a Data Set Updating with Incremental Values Understanding the Differences between Updating and Merging Handling Missing Values Day 12: Input SAS Data Set for Examples Modifying a SAS Data Set: The Simplest Case Modifying a Master Data Set with Observations from a Transaction Data Set Understanding How Duplicate BY Variables Affect File Update Handling Missing Values Introduction to Conditional Processing from Multiple SAS Data Sets Input SAS Data Sets for Examples Determining Which Data Set Contributed the Observation Combining Selected Observations from Multiple Data Sets Performing a Calculation Based on the Last Observation Day 13: Introduction to Analysing Your SAS Session with the SAS Log Understanding the SAS Log Locating the SAS Log Understanding the Log Structure Writing to the SAS Log Suppressing Information to the SAS Log Changing the Log’s Appearance Introduction to Directing SAS Output and the SAS Log Input File and SAS Data Set for Examples Routing the Output and the SAS Log with PROC PRINTTO Storing the Output and the SAS Log in the SAS Windowing Environment Redefining the Default Destination in a Batch or Non interactive Environment Introduction to Diagnosing and Avoiding Errors Understanding How the SAS Supervisor Checks a Job Understanding How SAS Processes Errors Distinguishing Types of Errors Diagnosing Errors Using a Quality Control Checklist Day 14: Introduction to Creating Detail and Summary Reports with the REPORT Procedure Understanding How to Construct a Report Input File and SAS Data Set for Examples Creating Simple Reports Creating More Sophisticated Reports Day 15: Introduction to Proc means Deriving descriptive statistics Introduction to Proc univariate and various options Day 16: Introduction to Proc freq Calculating counts using Freq Outputting the counts into a dataset Proc Transpose introduction Using VAR, ID and BY statement efficiently in transpose Reshaping the data with required variables Day 17: Introduction to Producing Charts to Summarize Variables Understanding the Charting Tools Input File and SAS Data Set for Examples Charting Frequencies with the CHART Procedure Customizing Frequency Charts Creating High-Resolution Histograms Day 18: Introduction to Writing Lines to the SAS Log or to an Output File Understanding the PUT Statement Writing Output without Creating a Data Set Writing Simple Text Introduction to the Basics of Understanding and Customizing SAS Output Understanding Output Input SAS Data Set for Examples Locating Procedure Output Making Output Informative Controlling Output Appearance Controlling the Appearance of Pages Representing Missing Values Day 19: Introduction to Customizing SAS Output by Using the Output Delivery System Input Data Set for Examples Understanding ODS Output Formats and Destinations Selecting an Output Format Creating Formatted Output Day 20: Proc Format introduction Creating format catalogue Converting catalogue to dataset Storing formats permanently and finding out formats in a library Accessing a Permanent SAS Data Set with User-Defined Formats ADVANCED SAS MODULES Day 21: Getting Started with the Macro Facility Replacing Text Strings Using Macro Variables Generating SAS Code Using Macros More Advanced Macro Techniques Other Features of the Macro Language Introduction to SAS Programs and Macro Processing How SAS Processes Statements without Macro Activity How SAS Processes Statements with Macro Activity Introduction to Macro Variables Macro Variables Defined by SAS Macro Variables Defined by Users Using Macro Variables Displaying Macro Variable Values Referencing Macro Variables Indirectly Manipulating Macro Variable Values with Macro Functions Introduction to Macro Processing Defining and Calling Macros How the Macro Processor Compiles a Macro Definition How the Macro Processor Executes a Compiled Macro Summary of Macro Processing Day 22: Introduction to the Scopes of Macro Variables Global Macro Variables Local Macro Variables Writing the Contents of Symbol Tables to the SAS Log How Macro Variables Are Assigned and Resolved Introduction to Macro Expressions Defining Arithmetic and Logical Expressions How the Macro Processor Evaluates Arithmetic Expressions Day 23: Introduction to Macro Quoting Deciding When to Use a Macro Quoting Function and Which Function to Use Using Various Macro Functions %STR and %NRSTR Functions etc Using the %BQUOTE and %NRBQUOTE Functions Referring to Already Quoted Variables Deciding How Much Text to Mask with a Macro Quoting Function Using %SUPERQ Summary of Macro Quoting Functions and the Characters They Mask Unquoting Text How Macro Quoting Works Other Functions That Perform Macro Quoting Day 24: Introduction to Storing and Reusing Macros Saving Macros in an Auto call Library Saving Macros Using the Stored Compiled Macro Facility General Macro Debugging Information Troubleshooting Your Macros Debugging Techniques Introduction to Writing Efficient and Portable Macros Keeping Efficiency in Perspective Writing Efficient Macros Writing Portable Macros PROJECT CONTENT COVERED Day Creation of Efficacy tables. Creation of Standard and safety tables. Day 28 Creation of listings Day Creation of Graphs a)Bar Charts b)Scatter plot c)Line plot d)Box plot Day 31 Creation of Analysis datasets/derived datasets Day 32 Introduction to SDTM CRF Annotation (ONLY BASICS) Introduction to mapping specification (ONLY BASICS) Introduction to SDTM dataset Creation (ONLY BASICS) Validation in Open CDISC (ONLY BASICS) Day 33 Introduction to ADAM Standards (ONLY BASICS) Mock interview and providing assistance for interview preparation Contact:

COBOL: • Introduction to COBOL The Structure of COBOL Programs Declaring data in COBOL Basic Procedure Division commands • Command Structure Selection in COBOL Iteration in COBOL • Simple Sequential Files Introduction to Sequential files Processing Sequential files Reading Sequential Files Counting records in a Sequential File • Advanced data declaration Edited Pictures The USAGE clause • Advanced Sequential Files Writing records to a Sequential File Inserting records in a Sequential File COBOL print files and variable-length records Sorting and Merging Updating a Sequential File Sorting a Sequential File • Direct Access Files Introduction to direct access files Relative Files Indexed Files •COBOL tables Using tables Creating tables - syntax and semantics Searching tables • Constructing large systems Contained and external sub-programs The COPY verb • COBOL string handling Inspect String Unstring Reference modification and Intrinsic Functions

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BASE SAS MODULES Day 1: Introduction to the SAS System Components of Base SAS Software Output Produced by the SAS System Ways to Run SAS Programs Running Programs in the SAS Windowing Environment Introduction to DATA Step Processing The SAS Data Set introduction How the DATA Step Works: A Basic Introduction Supplying Information to Create a SAS Data Set Introduction to Raw Data Examine the Structure of the Raw Data: Factors to Consider Reading Unaligned Data Reading Data That Is Aligned in Columns Reading Data That Requires Special Instructions Reading Unaligned Data with More Flexibility Mixing Styles of Input Day 2: Introduction to Beyond the Basics with Raw Data Using INFILE statement and various options. Testing a Condition before Creating an Observation Creating Multiple Observations from a Single Record Reading Multiple Records to Create a Single Observation Problem Solving: When an Input Record Unexpectedly Does Not have enough values Day 3: Introduction to Starting with SAS Data Sets Understanding the Basics Input SAS Data Set for Examples Reading Selected Observations Reading Selected Variables Creating More Than One Data Set in a Single DATA Step Using the DROP=, KEEP= and WHERE= Data Set Options for Efficiency Introduction to DATA Step Processing Input SAS Data Set for Examples Adding Information to a SAS Data Set Defining Enough Storage Space for Variables Conditionally Deleting an Observation Day 4: Introduction to Working with Numeric Variables About Numeric Variables in SAS Input SAS Data Set for Examples Calculating with Numeric Variables Comparing Numeric Variables Storing Numeric Variables Efficiently Numeric Functions. Day 5: Introduction to Working with Character Variables Input SAS Data Set for Examples Identifying Character Variables and Expressing Character Values Handling Missing Values Creating New Character Values Saving Storage Space by Treating Numbers as Characters Character Functions Day 6: Introduction to Acting on Selected Observations Input SAS Data Set for Examples Selecting Observations Constructing Conditions Comparing Characters Introduction to Creating Subsets of Observations Input SAS Data Set for Examples Selecting Observations for a New SAS Data Set Conditionally Writing Observations to One or More SAS Data Sets Day 7: Introduction to Working with Grouped or Sorted Observations Input SAS Data Set for Examples Working with Grouped Data Working with Sorted Data Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Day 8: Introduction to Using More Than One Observation in a Calculation Input File and SAS Data Set for Examples Accumulating a Total for an Entire Data Set Obtaining a Total for Each BY Group Writing to Separate Data Sets Using a Value in a Later Observation Introduction to Working with Dates Understanding How SAS Handles Dates Input File and SAS Data Set for Examples Entering Dates Displaying Dates Using Dates in Calculations Using SAS Date Functions Comparing Durations and SAS Date Values Day 9: Introduction to Combining SAS Data Sets Definition of Concatenating Definition of Interleaving Definition of Merging Definition of Updating Definition of Modifying 237 Comparing Modifying, Merging, and Updating Data Sets Day 10: Introduction to Concatenating SAS Data Sets Concatenating Data Sets with the SET Statement Concatenating Data Sets Using the APPEND Procedure Choosing between the SET Statement and the APPEND Procedure. Introduction to Interleaving SAS Data Sets Understanding BY-Group Processing Concepts Interleaving Data Sets Day 11: Introduction to Merging SAS Data Sets Understanding the MERGE Statement One-to-One Merging Match-Merging Choosing between One-to-One Merging and Match-Merging Introduction to Updating SAS Data Sets Understanding the UPDATE Statement Understanding How to Sel

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HADOOP trainers Required in elegant it services good salary in partime • Introduction to Big Data and Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • HBASE Concepts • Mongo DB Concepts • Sqoop Concepts • Real Life Use Cases Introduction to Big Data and Hadoop • What is Big Data? • What are the challenges for processing big data? • What technologies support big data? • What is Hadoop? • Why Hadoop? • History of Hadoop • Use Cases of Hadoop • Hadoop eco System • HDFS • Map Reduce • Statistics Understanding the Cluster •Typical workflow • Writing files to HDFS • Reading files from HDFS • Rack Awareness • 5 daemons Let's talk Map Reduce • Before Map reduce • Map Reduce Overview • Word Count Problem • Word Count Flow and Solution • Map Reduce Flow • Algorithms for simple problems • Algorithms for complex problems Developing the Map Reduce Application • Data Types • File Formats • Explain the Driver, Mapper and Reducer code • Configuring development environment - Eclipse • Writing Unit Test • Running locally • Running on Cluster • Hands on exercises c • Anatomy of Map Reduce Job run • Job Submission • Job Initialization • Task Assignment • Job Completion • Job Scheduling • Job Failures • Shuffle and sort • Oozie Workflows • Hands on Exercises Map Reduce Types and Formats • MapReduce Types • Input Formats - Input splits & records, text input,binary input, multiple inputs & database input. • Output Formats - text Output, binary output, multiple outputs, lazy output and database output • Hands on Exercises. Map Reduce Features •Counters • Sorting • Joins - Map Side and Reduce Side • Side Data Distribution • MapReduce Combiner • MapReduce Partitioner • MapReduce Distributed Cache • Hands Exercises Hive and PIG • Fundamentals • When to Use PIG and HIVE • Concepts • Hands on Exercises HBASE • CAP Theorem • Hbase Architecture and concepts • Programming and Hands on Exercises Case Studies Discussions Thanks&Regards Elegant IT Services, #nd Floor,Aswath Nagar Varthur main road,Near Railway Fly Over Maratha halli,Land mark: Chemmunar Jewellers,

Learn in just One month Big Data Hadoop,Hadoop,Hadoop by Industry experts in Elegant it Introduction to Big Data and Hadoop • Hadoop ecosystem - Concepts • Hadoop Map-reduce concepts and features • Developing the map-reduce Applications • Pig concepts • Hive concepts • HBASE Concepts • Mongo DB Concepts • Sqoop Concepts • Real Life Use Cases Introduction to Big Data and Hadoop • What is Big Data? • What are the challenges for processing big data? • What technologies support big data? • What is Hadoop? • Why Hadoop? • History of Hadoop • Use Cases of Hadoop • Hadoop eco System • HDFS • Map Reduce • Statistics Understanding the Cluster •Typical workflow • Writing files to HDFS • Reading files from HDFS • Rack Awareness • 5 daemons Let's talk Map Reduce • Before Map reduce • Map Reduce Overview • Word Count Problem • Word Count Flow and Solution • Map Reduce Flow • Algorithms for simple problems • Algorithms for complex problems Developing the Map Reduce Application • Data Types • File Formats • Explain the Driver, Mapper and Reducer code • Configuring development environment - Eclipse • Writing Unit Test • Running locally • Running on Cluster • Hands on exercises c • Anatomy of Map Reduce Job run • Job Submission • Job Initialization • Task Assignment • Job Completion • Job Scheduling • Job Failures • Shuffle and sort • Oozie Workflows • Hands on Exercises Map Reduce Types and Formats • MapReduce Types • Input Formats - Input splits & records, text input,binary input, multiple inputs & database input. • Output Formats - text Output, binary output, multiple outputs, lazy output and database output • Hands on Exercises. Map Reduce Features •Counters • Sorting • Joins - Map Side and Reduce Side • Side Data Distribution • MapReduce Combiner • MapReduce Partitioner • MapReduce Distributed Cache • Hands Exercises Hive and PIG • Fundamentals • When to Use PIG and HIVE • Concepts • Hands on Exercises HBASE • CAP Theorem • Hbase Architecture and concepts • Programming and Hands on Exercises Case Studies Discussions Thanks&Regards Elegant IT Services, #nd Floor,Aswath Nagar Varthur main road,Near Railway Fly Over Maratha halli,Land mark: Chemmunar Jewellers, Bangalore -

Syllabus- Course Objective Summary During this course, you will learn: Introduction to Big Data and Hadoop Hadoop ecosystem - Concepts Hadoop Map - reduce concepts and features Developing the map - reduce Applications Pig concepts Hive concepts Oozie workflow concepts HBASE Concepts Real Life Use Cases Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco Syst em HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Let's talk Map Reduce Before Map reduce Map Reduce Overview Word Count Problem Word Count Flow and Solution Map Reduce Flow Algorithms for simple & Complex problems Developing the Map Reduce Application Data Types File Formats Explain the Driver, Mapper and Reducer code Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster Hands on exercises How Map - Reduce Works Anatomy of Map Reduce Job run Job Submission Job Initialization Task Assignment Job Completion Job Scheduling Job Failures Shuffle and sort Oozie Workflows Hands on Exercises Map Reduce Types and Formats Map Reduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output Hands on Exercises Map Reduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hands Exercises Hive and PIG Fundamentals When to Use PIG and HIVE Concepts Hands on Exercises HBASE CAP Theorem  Introducti on to NOSQL Hbase Architecture and concepts Programming and Hands on Exercises Case Studies Discussions Certification Guidance Fee- INR+100 INR Registration Duration-45 hours(weekdays & weekends) Online training available on request Get trained on latest technology by ZEN industry expert. Technology: Java-SCJP/OCJP/Hibernate/Struts/Sprint etc.NET- VB.Net/C#/ASP.net/ MVC frarmrework etc Big data/Hadoop etc ETL/ data Stage/SQL Oracle// DBA/App / forms & reports etc C,C++ PHP/HTML5/javascript/JQuery/AJAX/AngularJS etc For other course like software testing, java, PHP, web technologies, Mobile application using Android/iOS and phone GAP please visit our office or contact us on given number Zeuristech Enterprise Networks Pvt. Ltd.,-ZEN 2nd Floor, Saikar Complex,Beside Ginger Hotel Bhumkar Chowk -pune- Land Mark- ICICI/AXIS Bank ATM Building

Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? Distribution systems. What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco System HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Developing the Map Reduce Application Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster MapReduce workflows How MapReduce Works Anatomy of a MapReduce job run Failures Job Scheduling Shuffle and Sort Task Execution MapReduce Types and Formats MapReduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output MapReduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hive and PIG Fundamentals When to Use PIG and HIVE Concepts

Introduction to Big Data and Hadoop What is Big Data? What are the challenges for processing big data? What technologies support big data? Distribution systems. What is Hadoop? Why Hadoop? History of Hadoop Use Cases of Hadoop Hadoop eco System HDFS Map Reduce Statistics Understanding the Cluster Typical workflow Writing files to HDFS Reading files from HDFS Rack Awareness 5 daemons Developing the Map Reduce Application Configuring development environment - Eclipse Writing Unit Test Running locally Running on Cluster MapReduce workflows How MapReduce Works Anatomy of a MapReduce job run Failures Job Scheduling Shuffle and Sort Task Execution MapReduce Types and Formats MapReduce Types Input Formats - Input splits & records, text input, binary input, multiple inputs & database input Output Formats - text Output, binary output, multiple outputs, lazy output and database output MapReduce Features Counters Sorting Joins - Map Side and Reduce Side Side Data Distribution MapReduce Combiner MapReduce Partitioner MapReduce Distributed Cache Hive and PIG Fundamentals When to Use PIG and HIVE Concepts HBASE CAP Theorem Hbase Architecture and concepts Programming

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Oracle DBA is certification oriented course which covers FIVE major parts as: 1. UNIX 2. PL/ SQL 3. DBA Admin Part1 on 11g 4. DBA Admin Part2 on 11g 5. Real Application Cluster (RAC) Syllabus: *** UNIX Fundamentals Architecture Commands File System The vi Editor The SHELL & Shell Scripting ***PL/ SQL Creating and altering tables and views Writing and running PL/ SQL programs from SQL*Plus or SQL Developer Using SQL statements within PL/ SQL Conditional execution and loop constructs Triggers, Cursors Trapping and handling errors and exceptions in code Implementing nested and labeled loops and blocks Exceptions Handling PL/ SQL records and tables ***DBA Admin1 on 11g Installing and Configuring Oracle 11g Creating and Managing Database Storage Structures Managing Users, Profiles, Privileges and Roles Maintaining Database Security Monitoring the Performance of the Database Backing Up and Recovering the Database *** DBA Admin2 on 11g Planning a backup strategy and a disaster recovery strategy Altering a database to ARCHIVELOG and NOARCHIVELOG modes Performing online and offline backups Recovering a database from non-critical losses Performing logical backups with the export and import utilities Reviewing database logs for diagnostic purposes Automating management tasks with the scheduler ***Real Application Cluster (RAC) Installing and configuring an Oracle 11g RAC Database Administering and Monitoring a RAC database using Enterprise Manager and command line tools Using configuration and management tools for RAC databases Administering ASM using command line and GUI clients Setting up services for workload management and application high availability Backing up, restoring and recovering a RAC database Creating duplicate and standby databases in a RAC Environment Monitoring and tuning the performance of a RAC database Faculty: We are having world class faculty having 8+ years of experience in the DBA field. Two certifications are: Paper I: OCA: Oracle Certified Associates Paper II: OCP: Oracle Certified Professional Duration of this course would be approx 5. 5-6 months. Batch Timings would be Morning:- 7 AM to 9AM Evening:- 7 PM to 9PM Contact details: Hemant Dhole , Cympac Software Solution Pvt Ltd Office No.15,First Floor,Punit-Yash Arcade,Karve Road,Near Kothrud Stand,Kothrud- SysAdminExperts - Pune

GET ACCOUNTANT JOB? JOIN BOOK-KEEPING AND ACCOUNTING COURSE Learn to write books of accounts manually and get job in the field of business & finance. Manual Accounting I Basic & Advance Accounting Principle, GAAP Preparation of Journals, Ledgers & Trial Balance Rectification of errors, Bills of Exchange, Asset Accounting, Bank Reconciliation Statement (BRS), Consignment, JV., Depreciation, Provisions & Reserves Finalization of Accounts of proprietorship, partnership and joint stock companies II Project Source Documents, Supporting/Accounting Voucher, Vouchers Writing books of accounts: Cash Book, General Ledger-GL, Accounts Receivable -A/R, Accounts Payable-A/P, and Journal Proper Registers : Purchase, Sales, Return Inwards & Return Outwards Inventory Management - Stock Records, Stock Valuation Internal Check & Audit Year Ending process & Next year beginning process Preparation of Financial statements CALL: 9246884200 for more details

GET ACCOUNTANT JOB? JOIN BOOK-KEEPING AND ACCOUNTING COURSE Learn to write books of accounts manually and get job in the field of business & finance. Manual Accounting I Basic & Advance Accounting Principle, GAAP Preparation of Journals, Ledgers & Trial Balance Rectification of errors, Bills of Exchange, Asset Accounting, Bank Reconciliation Statement (BRS), Consignment, JV., Depreciation, Provisions & Reserves Finalisation of Accounts of proprietorship, partnership and joint stock companies II Project Source Documents, Supporting/Accounting Voucher, Vouchers Writing books of accounts: Cash Book, General Ledger-GL, Accounts Receivable -A/R, Accounts Payable-A/P, and Journal Proper Registers : Purchase, Sales, Return Inwards & Return Outwards Inventory Management - Stock Records, Stock Valuation Internal Check & Audit Year Ending process & Next year beginning process Preparation of Financial statements Accounting Software/Packages Offered: Quickbooks PRO, SAGE, Peachtree, MYOB, Tally, Focus, Wings, PACT, Dac-Easy, and many more..... Also offers: Ms-Office CALL: 9246884200 for more details VISIT IN PERSON AT THE GIVEN BELOW ADDRESS : IPCA Accounting Institute 206 Sakina Complex, Above Maharaja Sweets, Opp. meraj Hotel, Above Raymonds Shop, Mehdipatnam X Roads, Hyderabad - 500028.

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Roles and Responsibilities - preparing and delivering lessons to a range of classes of different ages and abilities; marking work, giving appropriate feedback and maintaining records of pupils' progress and development; researching new topic areas, maintaining up-to-date subject knowledge, and devising and writing new curriculum materials; preparing pupils for qualifications and external examinations; managing pupil behaviour in the classroom and on school premises, and applying appropriate and effective measures in cases of misbehaviour; supervising and supporting the work of teaching assistants, trainee teachers participating in and organising extracurricular activities, such as outings, social activities and sporting events; liaising with other professionals, such as learning mentors, careers advisers, educational psychologists and education welfare officers;

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