Become proficient in implementing sophisticated business and data analytics models using concepts of Data science, R Programming, Apache Mahout and Statistics and ProbabilityThis is a Combo Training Course that gives you full proficiency in Data Science so that you can build sophisticated Data Analytics Models. This Course has been developed with extensive inputs from industry experts. You will learn about Data acquisition, analysis, Machine Learning techniques, Statistical Methods,Probability Distributions, and such other Data Science skills.
There are no prerequisites for taking this Training Course.
This is a complete Training Course in the field of Data Science that can make you industry-ready. You will gain deep expertise in multiple technologies and platforms. This Course will equip you with the much-needed programming expertise in R, learn about Apache Mahout, and get to know the techniques of Statistics and Probability. All in all you will have the right skills to work in the Data Science field in the best companies around the world at top salaries.
Topics: Understanding of R statistical computing and graphics, the statistical packages, familiarity with different datatypes and functions, learning to deploy them in various scenarios, use SQL to apply ‘join’ function.
Topics: R Functions, code compilation and data in well-defined format called R-Packages, learn about R-Package structure, Package metadata and testing, CRAN (Comprehensive R Archive Network), Vector creation and variables values assignment.
Topics: R functionality, Rep Function, generating Repeats, Sorting and generating Factor Levels, Transpose and Stack Function.
Topics: Understanding various functions like Merge, Strsplit, understanding Matrices and Manipulation of Matrix, Row Sums
Topics: Deploying R for plotting graphs, pie charts, bar plots, histogram and understanding components of Pie Chart.
Topics: One Way Analysis of Variance, Two Way Analysis of Variance
Topics: Understanding K-Means Clustering, and the workings of Cluster Algorithm, the association rule mining affinity analysis for data mining and analysis and learning co-occurrence relationships.
Topics: Learn about dependent and independent variables, linear regression and scatter plots
Topics: The concepts of Logistic Regression, deploying Logistic Regression in R, set of examples and implementation.
Topics: What is Area under ROC Curve? R –Sensitivity & Specificity, R Open Database Connectivity, deploying ODBC Tables for reading data, application of Confusion Matrix for performance visualization.
Topics: Creating an integrated environment for deploying R on Hadoop platform, working with RHadoop, RMR package and R Hadoop Integrated Programming Environment, R programming for MapReduce jobs and Hadoop execution.
Topics: Classification and Recommendation, Clustering in Mahout, Pattern Mining, Understanding machine Learning, Using Model diagram to decide the approach, Data flow, Supervised and Unsupervised learning
Topics: Concept of Recommendation, Recommendations by E-commerce site, Comparison between User Recommendations and Item recommendation, Define recommenders and Classifiers, Process of Collaborative Filtering, Explaining Pearson coefficient algorithm, Euclidean distance measure, Implementing a recommender using map reduce
Topics: Defining Clustering, User-to-user similarity, Clustering Illustration, Euclidean distance measure, Distance measure vector, Understanding the process of Clustering, Vectorizing documents-Unstructured data
Topics: Document clustering, Sequence-to-sparse Utility, K-Mean Clustering
Topics: Terminology, Predictor and Target variable, Classifiable DataKey Challenges in Classification algorithm, Vectorizing Continuous data, Classification Examples, Logic Regression and its examples
Topics: Clustering, Clustering Process, Transaction Clustering, Different techniques of Vectorization, Distance measure, Clustering algorithm-K-MEAN, Clustering Application-1, Clustering Application-2, Sentiment Analyzer
Topics: Pearson Coefficient, Collaborative Filtering Process, Collaborative Filtering, Similarity Algorithms, Pearson Correlation, Euclidean Distance Measure -Frequent Pattern & Association rules, Frequent Pattern Growth
Topics: Introduction to Data Science, importance of Data Science, statistical and analytical methods, deploying Data Science for Business Intelligence, transforming data, machine learning and introduction to Recommender systems.
Topics: How Data Science solves real world problems, Data Science Project Life Cycle, principles of Data Science, introduction to various BI and Analytical tools, data collection, introduction to statistical packages, data visualization tools, R Programming, predictive modelling, machine learning, artificial intelligence and statistical analysis.
Topics: Boxplot in R programming, understanding distribution and percentile, identifying outliers, Rstudio Tool, various types of distribution like Normal, Uniform and Skewed.
Topics: Deploying machine learning for data analysis, solving business problems, using algorithms for searching patterns in data, relationship between variables, multivariate analysis, interpreting correlation, negative correlation.
Topics: Data Transformation key phases Data Mapping and Code Generation, Data Processing operation, data patterns, data sampling, sampling distribution, normal and continuous variable, data extrapolation, regression, linear regression model.
Topics: Data analysis, hypothesis testing, simple linear regression, Chi-square for assessing compatibility between theoretical and observed data, implementing data testing on data warehouse, validating data, checking for accuracy, data operational monitoring capabilities.
Topics: Various techniques of data modelling and generating algorithms, methods of business prediction, prediction approaches, data sampling, disproportionate sampling, data modelling rules, data iteration, and deploying data for mission-critical applications.
Topics: Working with large datasets in data warehouses, data clustering, grouping, horizontal & vertical slicing, data sharding in partitioning, clustering algorithms, K-means Clustering for analysing and data mining, exclusive clustering, hierarchy clustering, Mahout Clustering algorithm and Probabilistic Clustering, nearest neighbour search, pattern recognition, and statistical classification.
Topics: Introduction to R statistical computing and graphics, concepts, features and advantages of R, Big Data Hadoop familiarity, integrating R and Hadoop, basic architecture, framework, installing RImpala packages.
Topics: What is statistics?, How is this useful, What is this course for
Topics: Converting data into useful information, Collecting the data, Understand the data, Finding useful information in the data, Interpreting the data, Visualizing the data
Topics: Descriptive statistics, Let us understand some terms in statistics, Variable
Topics: Dot Plots, Histogram, Stemplots, Box and whisker plots, Outlier detection from box plots and Box and whisker plots
Topics: What is probability?, Set & rules of probability, Bayes Theorem
Topics: Probability Distributions, Few Examples, Student T- Distribution, Sampling Distribution, Student t- Distribution, Poison distribution
Topics: Stratified Sampling, Proportionate Sampling, Systematic Sampling, P – Value, Stratified Sampling
Topics: Cross Tables, Bivariate Analysis, Multi variate Analysis, Dependence and Independence tests ( Chi-Square ), Analysis of Variance, Correlation between Nominal variables
Project Title – Restaurant Revenue Prediction
Dataset – Sales
Project Description – This project involves predicting the sales of a restaurant on the basis of certain objective measurements. This project will give real time industry experience on handling multiple use cases and derive the solution. This project gives insights about feature engineering and selection.
Project 1 – Understanding Cold Start Problem in Data Science
Topics: This project involves understanding of the cold start problem associated with the recommender systems. You will gain hands-on experience in information filtering, working on systems with zero historical data to refer to, as in the case of launching a new product. You will gain proficiency in working with personalized applications like movies, books, songs, news and such other recommendations. This project includes the following:
Project 2 – Recommendation for Movie, Summary
Topics: This is real world project that gives you hands-on experience in working with a movie recommender system. Depending on what movies are liked by a particular user, you will be in a position to provider data-driven recommendations. This project involves understanding recommender systems, information filtering, predicting ‘rating’, learning about user ‘preference’ and so on. You will exclusively work on data related to user details, movie details and others. The main components of the project include the following:
Project – Data Analysis Project
Data – Sales
Problem Statement – It includes the following actions:
Topics: Understand the business solutions, Discussion with the warehouse team, Data Collection & Storage, Data Cleaning, Build a Hypothesis Tree around the business problem, Produce the final result.
In Intellipaat self-paced training program you will receive recorded sessions, course material, Quiz,related software’s and assignments.The courses are designed such that you will get real world exposure and focused on clearing relevant certification exam. After completion of training you can take quiz which enable you to check your knowledge and enables you to clear relevant certification at higher marks/grade also you will be able to work on the technology independently.
In Self-paced courses trainer is not available whereas in Online training trainer will be available for answering queries at the same time. In self-paced course we provide email support for doubt clearance or any query related to training also if you face some unexpected challenges we will arrange live class with trainer.
All Courses are highly interactive to provide good exposure. You can learn at your own place and at your leisure time. Prices of self-paced is training is 75% cheaper than online training. You will have lifetime access hence you can refer it anytime during your project work or job.
Yes, at the top of the page of course details you can see sample videos.
As soon as you enroll to the course, your LMS (The Learning Management System) Access will be Functional. You will immediately get access to our course content in the form of a complete set of previous class recordings, PPTs, PDFs, assignments and access to our 24×7 support team. You can start learning right away.
24/7 access to video tutorials and Email Support along with online interactive session support with trainer for issue resolving.
Yes, You can pay difference amount between Online training and Self-paced course and you can be enrolled in next online training batch.
Yes, we will provide you the link from where you can download the required software’s.
Please send an email . You can also chat with us to get an instant solution.
Intellipaat verified certificates will be awarded based on successful completion of course projects. There are set of quizzes after each couse module that you need to go through . After successful submission, official Intellipaat verified certificate will be given to you.
Towards the end of the Course, you will have to work on a Training project. This will help you understand how the different components of course are related to each other.
Classes are conducted via LIVE Video Streaming, where you get a chance to meet the instructor by speaking, chatting and sharing your screen. You will always have the access to videos and PPT. This would give you a clear insight about how the classes are conducted, quality of instructors and the level of Interaction in the Class.
Yes, We do keep launching multiple offers, please see offer page.
We will help you with the issue and doubts regarding the course. You can attempt the quiz again.
This course is designed for clearing the following certification exams:
The entire training course content is in line with respective certification program and helps you clear the requisite certification exam with ease and get the best jobs in the top MNCs.
As part of this training you will be working on real time projects and assignments that have immense implications in the real world industry scenario thus helping you fast track your career effortlessly.
At the end of this training program there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and helps you score better marks in certification exam.
Intellipaat R, Mahout and the Intellipaat Course Completion certificate will be awarded on the completion of Project work (on expert review)(upon expert review) and on scoring of at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.
You will get Lifetime access to high quality interactive tutorials along with life time access to complete Course Material .There will be 24/7 access to video tutorials with email support. If you stuck in any unexpected problem we will provide online interactive sessions with trainer for issue resolving.
We provide 24X7 support by email for issues or doubts clearance for Self-paced training.
In online Instructor led training, trainer will be available to help you out with your queries regarding the course. If required, the support team can also provide you live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock.
This course is designed for clearing Cloudera certification (CCP:DS). At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Intellipaat Course Completion certificate.
This course is designed for clearing Mahout Certification Exam . At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Intellipaat Course Completion certificate.
At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Intellipaat Course Completion certificate.
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