|Course or Certification Name||Category||Location||Mode of learning|
|Securityand Privacy for Big Data - Part 2||Big Data||Online self study|
|Big Data on Amazon Web Services||Big Data||Offline self study|
|Big Data Bootcamp||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Microsoft Professional Capstone : Big Data||Big Data||Offline self study|
|XLRI Executive Program in Data Science using Python, R & Excel||Data Science||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Tableau 10 Advanced Training: Master Tableau in Data Science||Tableau||Online self study|
|Postgraduate Diploma in Data Science||Data Science||Classroom|
|Data Science for Business Innovation||Data Science||Online self study|
|Spark, Scala and Storm combo||Big Data||Online self study|
|Machine Learning, Data Science and Deep Learning with Python||Data Science||Online self study|
|Microsoft Excel for Data analyst||Financial modelling||Online self study|
|Data Visualization & Business Intelligence Expert||Data Visualization||Online self study|
|Hadoop Analyst||Data Science||Online self study|
|Tableau 10 A-Z: Hands-On Tableau Training For Data Science!||Tableau||Online self study|
|Introduction to Data Science using PythonÂ||Data Science||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
This course sensitizes regarding privacy and data protection in Big Data environments. You will discover privacy preserving methodologies, as well as data protection regulations and concepts in your Big Data system. By the end of the course, you will be ready to plan your next Big Data project successfully, ensuring that all privacy and data protection related issues are under control. You will look at decent-sized big data projects with privacy-skilled eyes, being able to recognize dangers. This will allow you to improve your systems to a grown and sustainable level | If you are an ICT professional or someone who designs and manages systems in big data environments, this course is for you! Knowledge about Big Data and IT is advantageous, but if you are e.g. a product manager just touching the surface of Big Data and privacy, this course will suit you as well.
This course provides a tour through Amazon Web Services' (AWS) Big Data stack components, namely DynamoDB, Elastic MapReduce (EMR), Redshift, Data Pipeline, and Jaspersoft BI on AWS. AWS Kinesis is also discussed. All steps for creating an AWS account, setting up a security key pair and working with AWS Simple Storage Service (S3) are covered as well. Numerous demos are provided, demonstrating interaction through AWS components via Web browser user interfaces, command line, and desktop tools.
Big Data bootcamp will help you build the technical skills, mindset, and networks that launch amazing careers. Jigsawâ€™s innovative curriculum features an extensive range of valuable assets including preparatory skills support and an in-person, in-class immersive experience.
The Microsoft Professional Program for Big Data is a comprehensive curriculum that teaches you how to build big data solutions.In this capstone project, you will undertake challenges to design, implement, and document a big data solution based on what you have learned.
Businesses today are trying to engage with data science in one form or another. Unfortunately, only a few have been able to even grasp the idea of what constitutes data science, let alone implement it usefully and profitably. This course introduces its participants to the world of data science. The objective is to strip away all the distractions around data science â€“ codes, tools, etc., and teach the techniques using practical cases that can be understood and appreciated by someone with an elementary knowledge of mathematics. This course uses hands-on approach to data science where participants get to work with data sets to generate insights for businesses.
Ready to take your Tableau skills to the next level? Want to truly impress your boss and the team at work? This course is for you! Hours of professional Tableau Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for A nalytics of the REAL WORLD. In this course you will learn: How to use Groups and Sets to increase your work efficiency 10xEverything about Table Calculations and how to use their power in your analysisHow to perform Analytics and Data Mining in TableauHow to create Animations in TableauAnd much, much more! Each module is independent so you can start learning from wherever you see fit. The more you learn the better you will get. However, you can stop at any time you will still have a strong set of skills to take with you.
PG Diploma in Data Science program is designed to get the learners employed by providing them with a broad understanding of the basic and advanced concepts of Data Science. The Data Science training will enable learners to implement Big Data techniques using tools using R, Excel, Tableau, SQL, NoSQL, Hadoop, Pig, Hive, Apache Spark and Storm. The program is spread over 11 months (and is designed in such a way that students will be job-ready by the end of it). After completing the Data Science diploma, you will be considered as a strong and competent data scientist.
The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues. | The course covers terminology and concepts, tools and methods, use cases and success stories of data science applications. | The course explains what is Data Science and why it is so hyped. It discusses the value that Data Science can create, the main classes of problems that Data Science can solve, the difference is between descriptive, predictive and prescriptive analytics, and the roles of machine learning and artificial intelligence.
It is an all-in-course designed to give a 360 degree overview of real-time processing of unbound data streams using Apache Storm and creating applications in Spark using Scala programming. The major topics include concepts of Big Data world, Batch Analysis, Types of Analytics and usage of Apache Storm for real-time Big Data Analytics, Comparison between Spark and Hadoop and Techniques to increase your application performance, enabling high-speed processing.
New! Updated for Winter 2019 with extra content on feature engineering, regularization techniques, and tuning neural networks - as well as Tensorflow 2.0 support! Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That's just the average! And it's not just about money - it's interesting work too! If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive machine learning tutorial includes over 100 lectures spanning 14 hours of video , and most topics include hands-on Python code examples you can use for reference and for practice. Iâ?? ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesnâ??. Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. Itâ?? s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference. You won't find academic, deeply mathematical coverage of these algorithms in this course - the focus is on practical understanding and application of them. At the end, you'll be given a final project to apply what you've learned! The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning, AI, and data mining techniques real employers are looking for, including: Deep Learning / Neural Networks (MLP's, CNN's, RNN's) with TensorFlow and Keras Data Visualization in Python with MatPlotLib and Seaborn Transfer Learning Sentiment analysis Image recognition and classification Regression analysis K-Means Clustering Principal Component Analysis Train/Test and cross validation Bayesian Methods Decision Trees and Random Forests Multiple Regression Multi-Level Models Support Vector Machines Reinforcement Learning Collaborative Filtering K-Nearest Neighbor Bias/Variance Tradeoff Ensemble Learning Term Frequency / Inverse Document Frequency Experimental Design and A/B Tests Feature Engineering Hyperparameter Tuning ... And much more! There's also an entire section on machine learning with Apache Spark , which lets you scale up these techniques to "big data" analyzed on a computing cluster. And you'll also get access to this course's Facebook Group , where you can stay in touch with your classmates. If you're new to Python, don't worry - the course starts with a crash course. If you've done some programming before, you should pick it up quickly. This course shows you how to get set up on Microsoft Windows-based PC's, Linux desktops, and Macs. If youâ?? re a programmer looking to switch into an exciting new career track, or a data analyst looking to make the transition into the tech industry â?? this course will teach you the basic techniques used by real-world industry data scientists. These are topics any successful technologist absolutely needs to know about, so what are you waiting for? Enroll now! "I started doing your course in 2015... Eventually I got interested and never thought that I will be working for corporate before a friend offered me this job. I am learning a lot which was impossible to learn in academia and enjoying it thoroughly. To me, your course is the one that helped me understand how to work with corporate problems. How to think to be a success in corporate AI research. I find you the most impressive instructor in ML, simple yet convincing." - Kanad Basu, PhD
The course is known to be one of the most sought-after spreadsheet programs and is very versatile to use for creating sophisticated financial models, household budget maintenance ad designing complex dashboards. The training is perfect for experts from any field like operations, finance, information technology, MIS, Administration and Human relations. Moreover, the course is endowed with all the hard skills and concepts needed to kick start your data analyst career. The course also targets certain business situations and tenders a solution for the same. Additionally, it includes latest and best tool provided for data visualization.
Data Visualisation refers to the representation of data and information in visual forms. Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. | This course has been designed to provide the best learning methods in the industry so that candidates get to understand the essentials of data visualization and business intelligence | Designed professional experts, the course offers in-depth knowledge on how to create effective data visualizations and of the different forms of visualizations | The course also helps candidates get hands-on experience on some of the prominent tools like Tableau and QlikView | Upon completion of the course, a certificate is awarded
This training course is a comprehensive study of Big Data Analysis with Hadoop. The course topics include Introduction to Hadoop and its Ecosystem, MapReduce and HDFS, Introduction to Hive, Relational Data Analysis with Hive, Hive Data Management and Optimization. Further, it gives an Introduction to Pig, Basic Data analysis using Pig, Complex data Processing, Multi-Dataset Operations, Introduction to IMPALA, ELT Connectivity with Hadoop Ecosystem.
Learn data visualization through Tableau 10 and create opportunities for you or key decision makers to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks. You'll learn all of the features in Tableau that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully. Use Tableau to Analyze and Visualize Data So You Can Respond Accordingly Connect Tableau to a Variety of DatasetsAnalyze, Blend, Join, and Calculate DataVisualize Data in the Form of Various Charts, Plots, and Maps Convert Raw Data Into Compelling Data Visualizations Using Tableau 10 Because every module of this course is independent, you can start in whatever section you wish, and you can do as much or as little as you like. Each section provides a new data set and exercises that will challenge you so you can learn by immediately applying what you're learning. Content is updated as new versions of Tableau are released. You can always return to the course to further hone your skills, while you stay ahead of the competition. Contents and Overview This course begins with Tableau basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease. To be able to find trends in your data and make accurate forecasts, you'll learn how to work with data extracts and timeseries. Also, to make data easier to digest, you'll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations. In order to begin visualizing data, you'll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects. You'll even learn when it's best to join or blend data in order to work with and present information from multiple sources. Finally, you'll cover the latest and most advanced features of data preparation in Tableau 10, where you will create table calculations, treemap charts, and storylines. By the time you complete this course, you'll be a highly proficient Tableau user. You will be using your skills as a data scientist to extract knowledge from data so you can analyze and visualize complex questions with ease. You'll be fully prepared to collect, examine, and present data for any purpose, whether you're working with scientific data or you want to make forecasts about buying trends to increase profits.
This course will the first data science course in a series of courses. Consider this course as a 101 level course, where I don't go too much deep into any particular statistical area, but rather just cover enough to raise your curiosity in the field of Data Science and Analytics.