Online self-learning courses offer autonomy, allowing individuals to learn at their own pace. They provide structured training materials with review exercises to enhance understanding. Utilizing multimedia resources like videos and presentations, learners actively engage with the content. while flexibility enables customization of study schedules. This fosters an environment conducive to effective learning and skill development, accommodating personal commitments.
GoLogica offers a course that covers a range of introductory statistical topics, utilizing SAS programming to perform various analyses. The course emphasizes interpreting the results of these analyses, ensuring participants can derive meaningful insights from their data.
The training includes essential skills for creating analysis flow diagrams using the extensive toolset provided by SAS Enterprise Miner. This involves both exploratory data analysis, such as segmentation, association, and classification analyses, and predictive modeling, including decision trees, regression, and neural network models. These capabilities are crucial for uncovering patterns and making predictions based on data.
Participants will learn to use ready-to-apply procedures that handle a wide variety of statistical methods. These methods encompass simple descriptive statistics, data visualization, analysis of variance (ANOVA), regression, categorical data analysis, multivariate analysis, cluster analysis, and non-parametric methods. Each of these techniques is vital for different aspects of data analysis and helps in understanding and interpreting complex data sets.
The course ensures that learners can confidently apply these methods to real-world scenarios, using SAS to analyze and interpret data effectively. They will gain hands-on experience with SAS Enterprise Miner, developing the ability to build and evaluate models that support data-driven decision-making. This practical approach ensures that participants are not only familiar with the theoretical aspects of the analyses but also proficient in applying those using SAS tools.
By the end of the course, participants will be well-equipped with the knowledge and skills to conduct comprehensive data analyses using SAS. They will be capable of assembling analysis flow diagrams, performing exploratory and predictive analyses, and interpreting the results to provide actionable insights. This training is ideal for anyone looking to enhance their expertise in statistical analysis and data mining using SAS, whether for academic, professional, or research purposes.
Salary Trends:
According to ZipRecruiter, The average salary of an SAS Predictive Modelling Professional typically ranges from $126k to $134k PA. It’s depending on factors such as experience, location, and specific job responsibilities.
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SAS Predictive Modelling Curriculum
Accessing and Assaying Prepared Data
Introduction to Predictive Modelling with Decision Trees Introduction to Predictive Modelling with Regressions
Introduction to Predictive Modelling with Neural Networks and Other Modelling Tools Model Assessment
Model Implementation Introduction to Pattern Discovery Special Topics (Self-Study)
Case Studies (Self-Study)
Introduction to Statistics
Inferences for the Mean
Analysis of Variance
Regression and Regression Diagnostics
Categorical Data Analysis
Navigate the SAS windowing environment
Read various types of data into SAS data sets
Validate and clean SAS data sets
Create SAS variables and subset data
Combine SAS data sets
Create and enhance listing and summary reports
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 data variables
Use several of the business user applications in the platform for SAS Business Analytics
Create and Exploit dynamic value selection
Build advanced information maps using SAS information Map Studio
Create advanced SAS BI Dashboard applications
Produce advanced stored processes able to create dynamic data sources
Build schedule and distribute advanced reports
Consolidate information into a business reporting application
Describe the online analytical processing capabilities available in the SAS platform
Explore the basic functionality of the SAS integration with JMP
Examine the types of metadata created in the SAS platform
Register source data and target tables
Create jobs and explore the functionality of the job editor
Work with many of the various transformations
Enhance table relationships using integrity constraints keys and indexes
Work with slowly changing dimensions
Create custom transformation with the Transformation Generation Wizard
Document and deploy jobs
Administer SAS Data Integration Studio
Reviewing the Platform for SAS Business Analytics
Exploring the platform for SAS
Business Analytics overview
exploring the client tier
Middle tier
Server tier and data tier
Overview of administration tasks
Checking the state of SAS servers
Exploring the metadata server and repositories
Troubleshooting the metadata server
Identifying different types of SAS servers
Monitoring
Logging SAS servers and spanners
Troubleshooting SAS servers
Backing up metadata with the Backup Wizard
Exploring OMABAKUP
Scheduling backups
Backing up physical files
Exploring connection profiles
Using roles to control access to application
Functionality
Exploring SAS folders
Defining regular users and groups
Defining administrative users
Giving users access to servers
Registering libraries
Tables in the metadata
Updating table metadata
Pre-assigning libraries
Troubleshooting data access
Introduction to metadata security
Exploring metadata permission and predefined ACTs
Securing content in the folder tree and outside the folder tree
Creating additional ACTs
Replicating an entire repository
Promoting selected content
The GoLogica certification is widely acknowledged, enhancing the credibility of your resume and opening doors to high-level positions in leading multinational corporations globally.
At the end of this course, you will receive a course completion certificate which certifies that you have successfully completed GoLogica training in SAS Predictive Modelling technology.
You will get certified in SAS Predictive Modelling by clearing the online examination with a minimum score of 70%.
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SAS Predictive Modelling Objectives
• Data Detectives: Uncover hidden patterns and predict future trends to make smarter decisions.
• Business Brainiest: Turn data into real-world insights to give your business a winning edge.
• Marketing Mavens: Predict customer behavior and target your marketing campaigns like a pro.
• Risk Guardians: Build models to identify risks before they become problems.
• Data Dabblers: If you work with data and want to use it for future predictions, this course can be a game-changer!
• 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
• Define a SAS Enterprise Miner project and explore data graphically
• Modify data for better analysis results
• Data Analysis Core: Brush up on your data analysis fundamentals - hypothesis testing, data manipulation, and statistical measures are key.
• Basic Statistics: Understanding concepts like central tendency, dispersion, and correlation will give you a solid foundation.
• SAS Experience: Prior SAS knowledge can be a plus, but some courses cater to beginners.
• Programming: Basic programming in Python or R might be helpful in some courses, but not always required.
Linear Regression this algorithm is a fundamental technique used to predict a numerical value based on historical data. It establishes a linear relationship between the input variables and the target variable, allowing for the estimation of future probabilities.
• Predictive modeling uses various techniques to analyze data and forecast future outcomes. Here are some common types:
• Classification: This predicts a category or class something belongs to. For example, will an email be spam (yes/no) or predicting customer churn (active/inactive).
• Regression: This predicts a continuous value. This is common for tasks like sales forecasting or predicting house prices.
• Clustering: This group data points with similar characteristics together. This helps discover hidden patterns in unlabeled data.
• Time Series: This focuses on forecasting future values based on past trends in time-series data. For instance, predicting stock prices or website traffic.
• Outlier Detection: This identifies unusual data points that deviate significantly from the majority. This can be useful for fraud detection or finding equipment malfunctions.
Clustering isn't directly used for making predictions in the same way techniques like regression or classification are. However, it plays a helpful role in preprocessing data for predictive modeling and can also be used in exploratory data analysis for better understanding the data before applying other models. Here's how clustering aids in predictive modeling
Missing data is a hitch in modeling. You can ditch rows/columns with missing values (deletion), estimate missing values (imputation), or create new features based on amusingness (engineering).
Multicollinearity happens when features are too similar. It can mess up your model. You can ditch one of the correlated features, combine them, or use fancier techniques to manage it.
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Visit GoLogica website, locate the 'Certificates' section, follow the instructions to verify your course completion by completing the exam and Get more than 70% marks. And download your certificate.
I'll guide you through the certification process step-by-step, ensuring you're well-prepared and confident in your subject matter by clearing an exam.
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GoLogica have a 10+ year’s good track record in the training market. However, it was founded in 2013.
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Self-paced learning offers flexibility, personalized progress, and the ability to review materials at your own convenience.
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SAS Predictive Modelling rated
(4.0 / 5) based on 6 reviews.
Ramachandhra
SAS Predictive modelling helped me completing my projects and I development my skills and its worth spending time for this course.
Rodrigues
Thanks to GoLogica for helping me complete this course with ease and help to build my career.
Divya
Good course but lack of materials and improvement for trainer will help to understand it easily and would be more interesting.
Rajesh
Worth spending my leisure to learn this course and now am happy that it helped to boost my pay-scale.
Thanks gologica.
Vishnu
Accommodations not enough. Much more videos related to the course needed.
Joseph
This is a fantastic course it was a wonderful experience with the lectures. It was a little hard to learn at first but then after contacting the teachers a few times to clarify my doubts it was a very easy thanks to the wonderful staff.
