Data Mining and Statistical Pattern Recognition with R

Data mining uses a blend of all of the above and machine learning principles in order to discover hidden patterns from raw data using exploratory analysis.

Intermediate 0(0 Ratings) 2 Students Enrolled
Created By Acl Academy Last Updated Mon, 18-Nov-2019 English
What Will I Learn?

Curriculum For This Course
23 Lessons 00:00:00 Hours
Overview of R
6 Lessons 00:00:00 Hours
  • Basics of R Programming
  • Various apply() functions
  • String Manipulations
  • Packages & Libraries
  • Built-in and User defined Functions
  • Basic Summarization and Visualization of Data
  • Knowledge Discovery Databases (KDD)
  • Cross-Industry Standard Process for Data Mining
  • SEMMA (Sample, Explore, Modify, Model, Assess)
  • KDD vs. CRISP-DM vs. SEMMA
  • Importing Data to R
  • Data Processing: Cleaning, Integrating, Transformation and reduction
  • Introduction to Statistical Learning
  • Pattern Recognition with Regression Models
  • Classification: Logistic Model, Discriminant Models
  • Resampling Methods: Cross-validation, Bootstrap
  • Linear Model Selection and Regularization
  • Some Non-linear Cases
  • Tree-Based Methods
  • Support Vector Classifier & SVM
  • Bayesian Classifier, Naive Bayes & Bayesian Belief Networks
  • Pattern Recognition with Random Forest & Neural Network
  • Clustering Methods: K-Means, Hierarchical & PCA
Requirements
  • Concept of Statistics and Mathematics
  • Working knowledge of R
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Description

Why ACL?

ACL Academy offers right IT professional courses with competent and experienced IT trainers. We have a wide variety of IT courses, which includes both the latest and traditional technologies. From core programming languages like C/C++/Java, C#, dot net, SQL, to trending topics of data science with Python, R and big data, and also high-end tech courses like web development Django, Blockchain, DevOps, Cloud computing, AI and Machine Learning, IoT, Robotics & Automation.  Here we create career successful job-ready professionals with all-around the progress of candidates through resume preparation, job assistance, improved presentation, communication skills, and interview preparation techniques. Our intermingled learning approach combines classroom training, online classes, instructor-led live virtual classrooms, project work, and teaching assistants. We at ACL IT Academy understand and believe in building a personal relationship while helping you make your professional career.

You will experience state-of-the-art infrastructure Labs with audio-visual and tele-video conference aids. We arrange small class size for focused instruction with real-life project exposure. We also facilitate onsite library and web-based e-library and a students’ Learning Management System.

Course Overview

These actionable insights help to identify repeated occurrences of a particular event in the future, hence these are very valuable to product-based companies. More and more companies are taking the help of data science & data analytics to drive their business growth and gain an advantage over their competitors.

Career Opportunity

Data scientists are the best domain to focus on for analysts right now.

  • Data Scientists are very much wanted professionals in recently emerging domains like Big Data Analytics and IT. Experts are predicting that about 35-40 zettabytes of data will be in generated by 2020, and Data Science career opportunities will only increase in that time. Due to being a relatively newer domain, shortage of skilled data scientists has led to the huge demand for Data Scientists in start-ups as well as well-established companies.
  • <!--[if !supportLists]-->· A Glassdoor survey shows that Data scientists lead the salary packages among all analysts. The median salary for data scientists is about 6-7 LPA and there are over 2000 job openings posted on Glassdoor alone. These surveys also report high vacancies for these posts, due to the fast emergence of large amounts of data.
  • Data scientists have to learn various skills, therefore their employ ability extends to various profiles like Data architect, Data Analyst, Business Analyst, Data administrator, Business intelligence specialists, etc. Gaining employment as a Data Scientist is very easy. Data scientists also help in the development of machine learning algorithms & data trend visualizations.
  • Since data science requires mastery over several domains, skills required for this are also various. A good data scientist must be proficient in quick & critical thinking, deep learning & AI methodologies, coding with deep knowledge of statistics & linear algebra, & working knowledge of databases. Therefore, with data science, you gain expertise over a lot of fields.
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About The Instructor
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  • 7 Students
  • 35 Courses
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