Data Science Course Material

1. Advanced CertificateCourse in Practical DataScience Poweredby Inc.USA 100 days fast track trainingprogram to accelerate your career in Data Science World. Learn PRACTICAL DATA SCIENCE BecomeEmployable 100Days Class Room l Online l Instructor-Led IntensiveCoaching Batches : Weekdays 10am -6pm Weekends 10am -4pm Colaberryisaprovenleaderindatasciencetrainingandconsultingworld in the USA. Colaberry has transformed the lives of 4000+ professionalsin the USA to achieve their career goals in data analytics. For the first time Colaberry is coming to India with a Practical approach to data science training. Colaberry has created a unique model which is a combination of “Harvard Case" method with "Learn by doing" approach that transforms the way students learn DataScience. Collaborationwith The program starts with a problem statement where students will be taught how to address the problem and find a right solution for it. In the process students are encouraged to learn the concepts as well as apply them to the real-worldproblems.

2. About the Program and theApproach In today’s world. Data has become the most valuable commodity and there is everincreasingdemandforDataPractitionersacrossallIndustriestobeequipped with tools and skills set to mine, refine and take actionable insights. This data Science program has been designed by a group of industry leaders and experts to help both businesses and individuals put Data Science into practice. Let’s take a deep dive into the world of Data Science and transform from learner todoer. RamMohan Serial Entrepreneur, Infogrex-Colaberry IndiaInitiative. As we enter the 4th industrial revolution, our “Learn by Doing” programs and "AI driven" platforms will empowermillionsofyouthtopursuehighlylucrativecareersintheareasofdatascience,machinelearning, deep learning, computer vision and artificialintelligence. Standard Approach: High-touch instructor driven learning process whichinvolves lectures, readings, testsetc. Our approach: Hands on codingwith experimentation. Ram DhanYadav CEO - Colaberry,USA. National Training Laboratories, Bethel,Maine. “AsaCo-founderofColaberryandInitiatorofDataAnalyticstrainingprogramsin USA,WewereverysuccessfulincreatinguniquepedagogicalTeachingmethods that transformed 4000+ professional lives in USA. My dream is to bring similar teaching experience and success to the Indian students and IT professional fraternity”. AnandDasari Co-founder, Colaberry,USA. ColaberryTeam Paul Bilodeau Founder CEOatFiltered, Colaberry School of DataAnalytics, North-Eastern University,Boston, Tommy Haugh Delivery Manager@Colaberry Colaberry School of Data Analytics, Bentley University,Boston, John McBride Vice-President ofSales ColaberryInc., Boston University,Boston, Massachusetts,USA. AbigailJones BusinessDevelopmentManager Colaberry Inc., Boston, Massachusetts, USA.

3. RegressionmodelsinMachineLearning SupervisedModels Cross Validation and K-foldCV Linear Regression I -II Bias variance tradeoff More on Gradient Descent - Learning rate Polynomial Regression Generalized regressionmodels Regularization Logistic regression The Process of DataScience What is Data Science ? How to do Data Science? Python for DataScientists Introduction to Python. Introduction to Jupyter Notebooks. Data Structures in python. Dealing with strings anddates. Decision statements andloops. Libraries and functions. Creating re-usableprograms. Support Vector Machines -SVR Kernel tricks in SVMs andregularization General Discussion about kernels- unsupervised Gaussian kernel Decision trees for Regression Bagging & Random forests. Computations withNumpy. Data Analysis withPandas. Data Visualization withMatplotlib. Introduction to Stats Models (Pyth andSklearn. Classification models in Machine Learning Classification - Logistic Regression Multivariate Logistic Regression Naives BayesClassifier on) Decision trees and Random forestsfor Segmentation and Sensitivity Ana Stochastic Gradient Descent. Support Vector Machines - SVC. Gradient Boosting andXgboost. Classification. lysis. Data Handling 101 for DataScientists What is Data and Dataformats. Relational Data. SQL inPython. Dealing with CSVs, TIFFs & other file formats inPython. File i/o using Python. Data imports usingAPIs. Web Scraping usingPython. Unsupervisedmodels Merging data from varioussources. Unsupervised Models Dimensionality Reduction -PCA Single valuedecomposition K-meansClustering DBScan Heirarchical Clustering DataCleaning. Math & Stats for DataScience Introduction to set theory Introduction to linear algebra Probability I Probability II Introduction to Statistics Measures of centraltendency Outlier Analysis Distributions and associatedstatistics Statistics revisited Introduction to predictionmodels. Hackathon Hackathon!!!

4. o • Learn from Industry Experts and RenownedFaculty • Advance Machine Learning Platformwww.refactored.ai • Collaborative Learning Environment - International and Globalfaculty. • Real-time Case Studies andInternships. VenkatramanSwaminathan, B.E., MS (USA), MBA(Australia) ICT Professional andFaculty. Dr. VangaSrinivas Sr. DataScientist. Manikandan Sr.Data Scientist,Colaberry. Open and Interactive Sessions by GuestFaculty AnuragGarg Verisk Analytics / IIIT SeedFund NeilGogte IT Guru / KMIT &NGIT SuryaPuchala CEO, Zettamine Anand.S Gramener Prof.HargopalRao Visiting Professor, BITS, Hyderabad. BhatDittakavi Founder and CEO Variance.AI Dr. Sanjeeva Rao, Ph.D., International University of Contemporary Studies,USA. AbhinandanPrateek Technocrat, IIT,Mumbai Contactus +91 9347412456 040- 67714400/4444 info@infogrex.com InfogrexTechnologies Private Ltd. Plot No. 12, Second Floor, Silicon Valley, Image Gardens Road, Hitech City, Madhapur, Hyderabad - 500 081 www.infogrex.com