WHY ASPIRE ?

We are the Information Technology training division of Aspire Techsoft Pvt Ltd, an IT company founded in 2011.We are ranked among the software training institutes in the india. We are specialized in ERP, SAP, SAS, JAVA, Data Warehousing,Hadoop etc.

Kothrud Branch (Head Office)
  • Address: Malhar Building, Plot No 2, H. A. Colony,
    Paud Phata, Eardawana, Pune 38.
  • Phone:7058-198-728 / 7058-733-423
  • Email:[email protected]
Dange Chowk Branch
  • Address: Office No 108, 1st Floor, ABC Nirman Complex,
    Opp Macdonald, 16 No Stop, Near Dange Chowk, Pimpri Chinchwad, Pune - 33.
  • Phone:8856-033-664
  • Email:[email protected]

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Training Structure

Live Web

Features:

  • Get trained by experts.
  • Attend classes from anywhere right from your computer.
  • Get all the benefits of classroom training.
  • Get access to course recordings up to 20 business days.
  • Access to latest software for hands-on.
  • Live interaction with trainers & trainees of different locations.

    Live Web

    Audio Requirements:

    • You should have working speakers, so that you can listen properly.
    • You should have working mics, so that you can interact with trainers.
    • We recommend to have Headphones with mics.

    Live Web

    System Requirements:

    • Internet Explorer 9, Mozilla Firefox 34, Google Chrome 39 (JavaScript enabled) or the latest version of each web browser.
    • Windows 7, Windows 8 or later.
    • Cable modem, DSL, or better Internet connection.
    • Internet bandwidth 2 mbps(recommended).
    • Dual-core 2.4GHz CPU or faster with 2GB of RAM (recommended).

    Live Web

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        Machine Learning For Data Analyst

        SAS Machine Learning for Data Analysts brings in the capability to support the business and management with clear and insightful analysis on the data at hand. This includes data mining skills, advanced modelling techniques, testing and creating and explaining results in clear and concise reports.

        Course Outline:

        SAS Programming 1: Essentials

        • Navigate the SAS windowing environment
        • Navigate the SAS Enterprise Guide programming environment
        • Read various types of data into SAS data sets
        • Create SAS variables and subset data
        • Combine SAS data sets
        • Create and enhance listing and summary reports
        • Validate SAS data sets.
        SAS Programming 2: Data Manipulation Techniques

        • Control SAS data set input and output
        • Combine SAS data sets
        • Summarize, read, and write different types of data
        • Perform DO loop and SAS array processing
        • Transform character, numeric, and date variables.
        SAS Macro Language 1: Essentials

        • Perform text substitution in SAS code
        • Automate and customize the production of SAS code
        • Conditionally or iteratively construct SAS code
        • Use macro variables and macro functions.
        SAS SQL 1: Essentials

        • Query and subset data
        • Summarize and present data
        • Combine tables, including complex joins and merges
        • Create and modify table views and indexes
        • Replace multiple DATA and PROC steps with one SQL query.
        SAS Programming 3: Advanced Techniques and Efficiencies

        • Benchmark computer resource usage
        • Control memory, I/O, and CPU resources
        • Create and use indexes
        • Combine data horizontally
        • Use hash and hiter DATA step component objects and arrays as lookup tables
        • Compress SAS data sets
        • Sample your SAS data sets
        • Create and use SAS data views
        • Safely reduce the length of numeric variables
        • Create user-defined functions and informats.
        SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression

        • Generate descriptive statistics and explore data with graphs
        • Perform analysis of variance
        • Perform linear regression and assess the assumptions
        • Use diagnostic statistics to identify potential outliers in multiple regression
        • Use chi-square statistics to detect associations among categorical variables
        • Fit a multiple logistic regression model.
        Applied Analytics Using SAS Enterprise Miner

        • Define a SAS Enterprise Miner project and explore data graphically
        • Modify data for better analysis results
        • Build and understand predictive models such as decision trees and regression models
        • Compare and explain complex models
        • Generate and use score code

        The fees is inclusive of:

        • Fee: ₹2,41,000/-   ₹1,36,000+GST | Duration: 144 Hours.
        • Training & Digital Badge.
        • Course material.
        • 2 attempts of Global certification.

        Download Course Curriculum

        

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