Machine Learning with R Course Certification Training
Analytics profession is to grow to $51b by 2016 making Machine Learning and R the most in-demand skills of our times. This course on Machine Learning with R introduces you to Machine Learning Algorithms with R, to help business organizations take informed decisions.
Acadgild gets ranked as one of the Top 10 Worldwide Technology Boot Camps.
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48 Hours of Mentoring Sessions
2 hrs per Session | 200hrs of Assignments & Projects
Introduction to Machine Learning
Understand the learning system model, training, testing, performance, Machine learning structure and the various learning techniques.
Nearest Neighbor Classification
Know about the instance based classifiers, nearest-neighbor classifiers. Master the difference between lazy and eager learning, understand k-NN variations, learn how to determine the good value for k and when to consider nearest neighbors. Learn condensing nearest neighbor issues and nearest Bayes classification.
Naive Bayes Learning
Learn conditional probability, master the basics of the Bayesian theorem, Bayes classifier, model parameters, naive Bayes training, types of errors, sensitivity and specificity, ROC curve, holdout estimation and cross-validation.
Understand key requirements, decision tree as a rule set, how to create a decision tree and choosing attributes, ID3 heuristic, entropy, tree induction, splitting based on ordinal attributes. Determine the best split and the strength and weakness of decision trees.
Learn binary response regression model, linear regression output of proposed model and work on the problems with linear probability model. Understand logistic function, logistic regression, its interpretation, odds ratio, goodness of fit measures, confusion matrix.
Introduction to Cluster Analysis
Gain insight of types of data in cluster analysis, categorization of major clustering methods, partitioning methods, hierarchical methods, density-based methods, grid-based methods, model-based clustering methods and supervised classification.
Principal Component Analysis (PCA) and Forecasting Principles
Realize the curse of dimensionality, dimension reduction. Understand the importance of factor and component analysis, principal component analysis, basic time series and its components. Learn about the moving averages (simple & exponential), R'Â’s inbuilt function ts(), plotting of time series, business forecasting using moving average methods, the ARIMA model and the various application of ARIMA model in business.
Mentee can select project from predefined set of AcadGild projects or they can come up with their own ideas for their projects
Corporate Training Solutions
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Projects Which Students Will Develop
Bank Special Service
This project is based on a survey based on the special services offered by Banks in order to compete with their rivals.
Classification Model with Algorithms
This project aims at creating a classification models for mushroom data set with different classification algorithms.
Using MNIST Data
This project aims to classify handwritten digits using the famous MNIST data.
Clustering Wine data
This project aims at clustering the wine data to determine the quantities of 13 constituents found in each of the three types of wines grown in Italy.
Naave Bayes Classification Algorithm
This project aims at creating Naave Bayes classification algorithm to classify the people as republican and democrats.
The training provided is very good, especially on AngularJS. It would have been good if we have involved in the final project on AngularJs development. Overall the training met the expectation.
Software Developer at Oracle, Hyderabad
The way of ACADGILD Mentor , Krish Ram teach is easily understand and easy learning with good clarity about the subject knowledge along with practical examples.He always makes us to understand by giving real time and interesting examples.The support and co-operation from the team is great and i am feeling happy to doing course here.
Software Engineer-Web System at Quantum Inventions(QI), Kolkata
I joined AcadGild's Front End Development course about a month back. So far my experience has been great. And now I am really glad I took this course. The focus on coding while learning sessions and the bunch of tips after session to solve assignments gave the load hands on experience.
Senior Graphic Designer at Photon, Plano, Texas
I am Jayanth Kumar T, a Senior Research Engineer. I took up the Front End course at AcadGild. The course definitely helped me add skills to my resume.The mentors were disciplined, knowledgeable and provided a good support. Thank you all for the support during the course.
Software Developer at Oracle, Hyderabad
My name is Vyshali Bhat. My mentor, Mr. Jayant has been very supportive and it was a very good learning experience for me. I wish to thank the Acadgild team for all the support and guidance.
Machine learning is the science of getting computers to act without being explicitly programmed. In this course, you will learn about the most effective machine learning techniques and gain experience by implementing them and getting them to work for you. More importantly, you'll learn about not only the theoretical part but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI (Artificial Intelligence)
This course provides a broad introduction to machine learning, data mining and statistical and pattern recognition. The course will also enable you to implement numerous case studies and applications so that you'll also learn how to apply learning algorithms. It is the world’s most powerful programming language for statistical computing and graphics making it a must for Data Scientists.
Did you know R-programming is one of the most important tools in the field of Machine Learning and analytics? Companies like Facebook, Google, Ford Motors, Lloyd and so many more rely on insights from Machine Learning. Want to know more about such organization? Browse through our blog.
Did you know that Spark is a very important contributor in the field of Machine Learning? In this series of ‘Machine Learning with Spark’, we provide you, with a step by step guidance on using Spark in Machine Learning.
Data can be communicated through different means, a very effective way to do is using visual graphics. Now, do you know how data can be explained graphically using R? Find this out with our blog 'Exploratory Data Analysis'