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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Big Data for Reliability and Security program will be teaching the students the key practices and principles of big data for developing and improving the security and reliability of computing systems. The students will be learning about the big data technology that is at present changing the way of doing business and transactions. The Online Certification Course on Big Data for Reliability and Security by edX will deal with the various techniques that pertain to computer science.
The curriculum includes - Flink, containers, spark streaming, apache-spark, Mesos, and apache. The techniques for solving various issues that currently exist in the computing world. The students will be provided with a set of challenging projects and assignments to solve. The Big Data for Reliability and Security training covers ways to analyze the data sheets that will be taught to the students. The participating candidates will be learning to formulate strategies and techniques. The various ways of presenting data will also be taught in the Big Data for Reliability and Security certification course.
Two different tracks for enrolling and learning the course are available on edX which may be opted for by the students. Both the tracks are self-paced but some major differences may considered before rolling. During the verified track, the candidates will have to submit some fee to start accessing the course for an unlimited period. In the same way, if someone chooses the audit track, they will be able to learn the programme without any cost.
The Highlights
- 6-week programme
- Free registration
- The course hosted by Purdue University
- Certificate by edX in Big Data for Reliability and Security programme
- Verified certificate
- Instructor-led course
Programme Offerings
- assignments
- E- learning
- Video transcripted
- Lectures
- Projects
- Expert Faculty
Courses and Certificate Fees
| Certificate Availability |
|---|
| no |
Eligibility Criteria
Education
To apply, the students need to have knowledge of the python programming language. They need to have basic knowledge of statistics and probability.
Note: The candidates who belong to the Cuba, Crimea region of Ukraine, and Iran can not apply because the US sanctions restrict the policies.
Certification Qualification Details
Big Data for Reliability and Security certification needs to be upgraded by the students for getting the registered certificate by paying the desired amount.
What you will learn
The students will have their skills developed in the following domains -
- The candidate will be formulating security strategies for formulating the production system.
- Learners will be taught about the topic of machine learning and with its help will be solving various cases under Big Data for Reliability and Security certification course.
- He/she will be learning about the data analytic techniques so that they can work on assignments.
- The students will understand the security measures and will work on improving the security of computing systems under the Big Data for Reliability and Security training.
- The participants will be constructing software artifacts for framing real-world database sets.
- The students will learn about neural building blocks while working on problem statements.
- The students will learn the various techniques that include both supervised and unsupervised methods.
- Big data processing mechanisms will be taught to the participants so that they can frame solution files under the Big Data for Reliability and Security program.
- The applicants will further develop skills in detecting the proximity of Bluetooth devices.
- The ways of manipulating video images using machine learning will also be covered by the participants with the Big Data for Reliability and Security training.
Who it is for
The program is for -
- Students who want to solve real-world cases operating in machine learning and big data structure should register for the program.
- The applicants who want to pursue a serious professional certificate in computer application can enrol in the Big Data for Reliability and Security course.
Application Details
The steps need to be followed precisely for the following The Big Data for Reliability and Security by edX program-
Step 1: Please visit the site of edX to find the application form-https://www.edx.org/learn/computer-programming/purdue-university-big-data-for-reliability-and-security
Step 2: The application form has the space given to mention the students “Full Name”. Please provide the details.
Step 3: The candidates have to give a “username” in the application form for creating their unique account.
Step 4: The mail address has to be provided by the candidate so that they can receive all the information.
Step 5: The students need to agree to the clauses before proceeding further.
Step 6: The students need to upgrade the Big Data for Reliability and Security certification course and click on the “Apply Now” button and access Big Data for Reliability and Security training certification syllabus
The Syllabus
- Applications of Big Data Analytics and Reliability and Security
- Big Data Processing
- System-Level View of Dependable Design
- Real-World Examples of Failures
- Terminology of Dependable Systems
- Attributes of Dependability Systems
- Means to Achieve Dependability
- Three Different Impairments in a System
- Fault Cycle
- Infrastructure Security
- Data Privacy
- Data Management and Data Monitoring
- Big Data Security Framework
- Centralization and De-Centralization
- Pre-Processing for Security
- Unsupervised Learning
Robustness of Machine Learning Models
Linear SVM and Binary Classifications
Non-Linear SVM
Pipeline to Apply Non-Linear SVM
Introduction to Neural Network and Canonical Use
Neural Network
Use of Neural Network in Computer Systems
How to Avoid Overfitting?
- Test Set Method
- Leave One Out Cross Validation (LOOCV)
- K-Fold Cross Validation
- Recap of Various Learning Techniques
- Adversarial ML
- Adversarial Evasion Attacks
- Defense Against Attacks
- Addressing Overfitting
- Bias-Variance Tradeoff
- Regression with Regularization
- Avoid Overfitting- Penalty Function
- Which One to Choose Between Ridge and Lasso Regression
- Feature Engineering
- Significant Feature Engineering Techniques
- Feature Extraction Concept
- Principal Component Analysis (PCA)
- Basics of Federated Learning
- Federated Learning in Practice
- Aggregation in Federated Learning
- Secure Aggregation
- Krum and Bulyan Secure Aggregation
- Model Poisoning Attack
- Defense Against Model Poisoning Attack
- Threat Model and Comparison of FL with Distributed Computing
- Differential Privacy