Data Science Architect Masters

Transcription

1 About Intellipaat Intellipaat is a fast-growing professional training provider that is offering training in over 150 most sought-after tools and technologies. We have a learner base of 600,000 in over 32 countries and growing. For job assistance and placement we have direct tie-ups with 80+ MNCs. Key Features of Intellipaat Training: Instructor Led Training Self-Paced Training Exercise and project work Lifetime Access 178 Hrs of highly interactive instructor led training 214 Hrs of Self-Paced session with Lifetime access 356 Hrs of real-time projects after every module Lifetime access and free upgrade to latest version Support Lifetime 24*7 technical support and query resolution Get Certified Get global industry recognized certifications Job Assistance Job assistance through 80+ corporate tie-ups Flexi Scheduling Attend multiple batches for lifetime & stay updated. About the Course Our Data Science Architect masters course lets you gain proficiency in Data Science. You will work on real-world projects in Data Science with R, Apache Spark, Scala, Deep learning, Tableau, Data Science with SAS, Hadoop developer and more. In this program, you will cover 9 courses and 27 industry-based projects. Instructor Led Duration 178 Hrs Weekend Batch 3 Hrs/Session Self Paced Duration 214 Hrs

2 Why take this Course? Intellipaat s Data Science Architect Masters Course will provide you in-depth knowledge on data science, real-time analytics, statistical computing, parsing machine-generated data and finally the domain of Deep Learning in artificial intelligence, also learn how to leverage Big Data platforms like Hadoop for data science. This program is specially designed by Industry experts. Course Curriculum Data Science with R: Module /Topic Hands-on exercises Introduction to Data Science and Statistical Analytics Introduction to R R studio & its environment Introduction, Basic Operations, Conditional Statements Control flow statements Data Exploration, Data Wrangling, and R Data Structure Data Types in R Data Structures in R (vector, list, complex, data frame etc) Importing files (text, csv, db, JSON) Functions in R (build-in & custom functions) Data Wrangling (subset, NA imputation, sampling data into test and train, Normalization) Data Visualization Visualization importance Graphs with the base package: Bar Graph, Line Graph, box plot, scatter plot ggplot2 package: Bar graph, line graph, box plot, scatter plot, color & shape importance Introduction to Statistics Hypothesis Testing (z-score, t-test, chi-square

3 test) using R Understand Mean, Median, Mode, variance & standard devication in R Learn probability, conditional probability, Confusion Matrix, Bayes Theorem Predictive Modeling - 1 ( Linear Regression) Data preprocessing Build a Linear Regression model using R Understand the results and evaluation Metrics (RMSE, MAPE) Predictive Modeling - 2 ( Logistic Regression) Create glm model, Prediction, the importance of Threshold Evaluation metrics for logistic, Accuracy, Precision, ROC curve analysis, Kappa metric Decision Trees Entropy, Information Gain rpart& C5.0 Decision Tree Algorithms Accuracy, Precision, Recall, F1 Score of classifier Random Forest Understanding Random forest with an example Unsupervised learning Clustering(Agglomerative or divisive), K-means clustering and graphs, Hierarchical clustering Association Analysis and Recommendation engine Building a recommendation engine using R Sentiment Analysis R code to get twites using Twitter API Sentiment Analysis of twites for either Positive sentiment or Negative sentiment Time Series Real-Time hands-on with stock price data of any

4 organization. Understand the Components of Time Series (Trend, Randomness, Seasonality) Build an ARIMA Model to predict the future stock price Python for Data Science: Module/Topic Introduction to Python Hands-on Exercises Install Anaconda Python distribution for your OS (Windows/Linux/Mac) Basic constructs of Python language Write your first Python program Write a Python Function (with and without parameters) Use Lambda expression Write a class, create a member function and a variable, Create an object Write a for loop to print all odd numbers Writing Object-Oriented Program in Python and connecting with Database File Handling, Exception Handling in Python Open a text file and read the contents Write a new line in the opened file Use pickle to serialize a python object, deserialize the object Raise an exception and catch it Mathematical Computing with Python (NumPy) Import numpy module, Create an array using ND-array, Calculate std deviation on an array of numbers, Calculate correlation between two variables Scientific Computing with Python (SciPy) Import SciPy

5 Apply Bayes theorem using SciPy on the given dataset Data Visualization (Matplotlib) Plot Line, Pie, Scatter, Histogram and other charts using Matplotlib Data Analysis and Machine Learning (Pandas) / Data Manipulation with Python Import Pandas Use it to import data from a JSON file Select records by a group and apply a filter on top of that View the records Perform Linear Regression analysis Create a Time Series Machine Learning, Natural Language Processing (Scikit-Learn) Setup Jupyter Notebook environment Load a dataset in Jupyter Use algorithm in Scikit-Learn package to perform ML techniques Train a model, Create a search grid Web Scraping for Data Science Install Beautifulsoup and lxml Python parser Make a Soup object using an input HTML file Navigate Py objects in the soup tree, Search tree, Print output Python on Hadoop Write a basic MapReduce Job in Python and connect with Hadoop Framework to perform the task Writing Spark code using Python Implement sandbox Run a python code in a sandbox Work with HDFS file system from the sandbox

6 Apache Spark &Scala: Introduction of Scala Pattern Matching Module /Topic Executing the Scala Code Classes concept in Scala Case classes and pattern matching Concepts of traits with an example Scala Java interoperability Scala collections Mutable Collections Vs. Immutable Collections Use case bobsrockets package Introduction to Spark Spark Basics Working with RDDs in Spark Aggregating Data with Pair RDDs Writing and Deploying Spark Application Parallel Processing Spark RDD Persistence Spark Streaming &Mlib Improving Spark Performance Spark SQL and Data Frames Scheduling / Partitioning AI and Deep Learning with TensorFlow: Module /Topic Introduction to Neural Networks Multi-layered Neural Networks Regularization techniques (L1, l2) CNN: Convolutional Neural Networks LSTM: Long Short-Term Memory Hidden Markov Chatbots

7 Tableau Desktop 10: Module / Topic Hands on Exercises Introduction to Data Visualization and Power of Tableau Architecture of Tableau Play with the tableau desktop, interface to learn its user interface, Share an existing work, Export an existing work Working with Metadata& Data Blending Connect to an excel sheet and import data, Use metadata and extracts, Handle NULL values, Clean up the data before the actual use, Perform various join techniques, Perform data blending from more than one sources Creation of sets Create and edit sets using Marks, Highlight desired items, Make groups, Applying sorting on the result, Make Hierarchies in the created set Working with Filters Add Filter on the dataset by date/dimensions/measures, Use the interactive filter to views, Remove some filters to see the result Organizing Data and Visual Analytics Apply labels, annotations, tooltips to graphs, Edit the attributes of axes, Set a reference line, Do k-means cluster analysis on a dataset Working with Mapping Plot latitude and longitude on geo map, Edit locations on the map, Create custom geocoding, Use images of a map and plot points on it, find coordinates in the image, Create a polygon map, Use WMS

8 Module / Topic Working with Calculations & Expressions Hands on Exercises Working with Parameters Create new parameters to apply on a filter, Pass parameters to filters to select columns, Pass parameters to filters to select charts Charts and Graphs Plot a histogram, heat map, tree map, funnel chart and others using the same data set Do market basket analysis on a given dataset Dashboards and Stories Create a dashboard view, Include objects, legends, and filters, Make the dashboard interactive Create and edit a story with visual effects, annotation, description Integration of Tableau with R and Hadoop Deploy R on the tableau, Create a line graph using R interface, Connect tableau with Hadoop and extract data Data Science with SAS: Module/Topic Introduction to SAS Hands-on Excercise Working with multiple data sets SAS Enterprise Guide Import Excel file in workspace Read data Export the workspace to save data SAS Operators & Functions Apply logical, arithmetic operators and SAS functions to perform operations

9 Compilation & Execution Using Variables Use KEEP and DROP statements Creation and Compilation of SAS Data sets Use delimiter rules on raw data files SAS Procedures Use SORT, FREQ, SUMMARY, EXPORT and other procedures Input statement and formatted input Read standard and non-standard numeric inputs with Formatted inputs Control while a record loads, Control a Line pointer, Write Multiple IN and OUT statements SAS FORMAT Format a variable, deploy format rule on PROC DATA set, Use ATTRIB statement SAS Graphs Plot graphs using PROC GPLOT Display charts using PROC GCHART Interactive Data Processing Working with interactive dashboards Data Transformation Function Use Functions in data transformation Output Delivery System (ODS) Optimize data, generate RTF, pdf, HTML and doc files SAS MACROS Write a macro Use positional parameters

10 PROC SQL Create SQL query to select and add a condition Use a CASE in select query Advanced Base SAS Use web UI to do statistical operations Summarization Reports Use PROC SORT to sort the results, List ODS, Find mean using PROC Means, print using PROC PRINT Web Scraping for Data Science Install Beautifulsoup and lxml Python parser Make a Soup object using an input HTML file Navigate Py objects in the soup tree, Search tree, Print output Python on Hadoop Write a basic MapReduce Job in Python and connect with Hadoop Framework to perform the task Writing Spark code using Python Implement sandbox Run a python code in a sandbox Work with HDFS file system from the sandbox Self-Paced Courses Statistics & Probability Hadoop Developer This Apache Hadoop Developer course will help you get a detailed idea about Big Data and Hadoop. Some of the topics included are an introduction to the Hadoop ecosystem, understanding of HDFS and MapReduce including MapReduce abstraction. Learn to install, implement various components of Hadoop like Pig, Hive, Flume, Sqoop, and YARN.

11 Advance Excel This Microsoft Excel course will give you an overview of working with the powerful spreadsheet application Excel. This includes creating dashboards, interactive components, data consolidation and debugging. This Training is useful for working on financial, mathematical and statistical data processing. Learning Path Project Work Course Industry/Domain Project General Understanding Cold Start Problem in Data Science Data Science Entertainment Recommendation for Movie, Summary With R E-commerce Making sense of Customer Buying Pattern Banking Fraud Detection in Banking System General Python web Scraping for Data Science Software Create a password generator Data Science Banking Impact of pre-paid plans on the preferences of investors with Python Banking Prediction of Stock prices Software Server logs/ Firewall logs

12 Apache Spark &Scala Deep Learning with TensorFlow Tableau 10 Desktop Data Science with SAS Media Internet Services Internet Services Internet Services General E-commerce Ecommerce Sales Crime Healthcare Retail Healthcare Sales Banking Analytics Movie Recommendation Twitter API integration for tweet analysis Data Exploration Using Spark SQL Wikipedia dataset Image recognition with Tensorflow Handwriting recognition with Neural Networks Building an AI-based Chatbot Ecommerce product recommendation Tableau Interactive Dashboards Segmenting types of crimes and their frequency The visual mapping between Vaccination rate and Measles outbreak Analysing market performance Categorization of patients based on a count of drugs for their therapy Build Revenue projections reports Impact of pre-paid plans on the preferences of investors k-means Cluster analysis on iris dataset Intellipaat Job Assistance Program Intellipaat is offering comprehensive job assistance to all the learners who have successfully completed the training. A learner will be considered to have successfully completed the training if he/she finishes all the exercises, case studies, projects and gets a minimum of 60% marks in the Intellipaat qualifying exam. Intellipaat has exclusive tie-ups with over 80 MNCs for placement. All the resumes of eligible candidates will be forwarded to the Intellipaat job assistance partners. Once there is a relevant opening in any of the companies, you will get a call directly for the job interview from that particular company. Frequently Asked Questions: Q 1. What is the criterion for availing the Intellipaat job assistance program? Ans. All Intellipaat learners who have successfully completed the training post April 2017 are directly eligible for the Intellipaat job assistance program. Q 2. Which are the companies that I can get placed in? Ans. We have exclusive tie-ups with MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, and more. So you have the opportunity to get placed in these top global companies.

13 Q 3. Does Intellipaat help learners to crack the job interviews? Ans. Intellipaat has an exclusive section which includes the top interview questions asked in top MNCs for most of the technologies and tools for which we provide training. Other than that our support and technical team can also help you in this regard. Q 4. Do I need to have prior industry experience for getting an interview call? Ans. There is no need to have any prior industry experience for getting an interview call. In fact, the successful completion of the Intellipaat certification training is equivalent to six months of industry experience. This is definitely an added advantage when you are attending an interview. Q 5. What is the job location that I will get? Ans. Intellipaat will try to get you a job in your same location provided such a vacancy exists in that location. Q 6. Which is the domain that I will get placed in? Ans. Depending on the Intellipaat certification training you have successfully completed, you will be placed in the same domain. Q 7. Is there any fee for the Intellipaat placement assistance? Ans. Intellipaat does not charge any fees as part of the placement assistance program. Q 8. If I don t get a job in the first attempt, can I get another chance? Ans. Definitely, yes. Your resume will be in our database and we will circulate it to our MNC partners until you get a job. So there is no upper limit to the number of job interviews you can attend. Q 9. Does Intellipaat guarantee a job through its job assistance program? Ans. Intellipaat does not guarantee any job through the job assistance program. However, we will definitely offer you full assistance by circulating your resume among our affiliate partners.

14 Q 10. What is the salary that I will be getting once I get the job? Ans. Your salary will be directly commensurate with your abilities and the prevailing industry standards. What makes us who we are? Data science training includes a lot of constituent components and the Intellipaat data science training provided the most comprehensive and in-depth learning experience. I really liked the projects in data science which were real world projects helping me take on a data science role in the real world that much easier. -Bhanukumar Muppalla I am glad I took the Intellipaat spark training. The trainers offered quality Spark training with real world examples and there was extensive interactivity throughout the training and this made the Intellipaat training the best according to me. -Anthony Crenshaw