'This Course covers SQL using Microsoft SQL Server 2019 and you can apply the logic of these SQL queries in Oracle, MySql, PostgreSQL, Microsoft Access, SQLite, MongoDB, IBM DB2, Redis, ElasticSearch, Cassandra, Splunk, MariaDB, Teradata, Hive, Solr, HBase, FileMaker, SAP HANA, Amazon DynamoDB, SAP Adaptive Server, Neo4J, CouchBase, Memcached, and Microsft Azure SQL'. "Welcome to the most popular Quality complete Course on Microsoft SQL Server(MS SQL Server)" Covers different forms of SELECT Statements Explains how to filter the Records All the Arithmetic operators are explained NULL Values are explained Beautiful examples of all the operators ORDER BY, GROUP BY, HAVING clauses has examples in detail The course covers all the Aggregate Functions and other Functions UNION and JOINs are explained with real-life examples I have explained all types of Joins Data types used in Microsoft SQL Keys and Constraints are explained in detail ====================================================================================== Join this course which is the best "Microsoft SQL" course. I will share all the syntax of SQL with multiple examples along the way!!! Want to start learning SQL from scratch with no previous coding experience? You have come to the right place. Please have a look at the Course content carefully and ask a few questions from yourself? I have shared all the codes which are used in this course Is the Course taught by a real-time expert? I have more than 15  years of experience as an Instructor and more than 10 years of experience in SQL . I firmly believe that if an Instructor does not have a good experience, he/she will flood the course with poor content. Is the Course content clear and Precise? The content is short, crisp, and clear. The course assumes no prior knowledge on MS SQL(Microsoft SQL Server) and teaches you from scratch to advanced level Once you Enroll for this Course, you get lifetime access to this course and you will get all the future updates. The course does not cover T-SQL directly but it will help you to learn T-SQL also. This will also help you to get Microsoft certification . This Course is not for DBA(Database Administration) but certainly, helps you to become better. If you plan to work with other databases like Oracle , MySQL , SQLite , PostgreSQL , etc, it will be extremely helpful. If you are a data scientist ( Data Analysis role ) or willing to become a data scientist, then SQL is a must and this course helps in data analytics . Do you want to start on SQL but have no experience with SQL? If you have some prior knowledge of SQL or if you are a complete fresher, you are at the right place. The Course teaches you to SQL right from Scratch. It will be the best course for absolute beginners. There’s no risk involved in taking this Course! I am sure that this is the best complete course on SQL and it is the perfect starting point to master complete Microsoft SQL. What if you are stuck? I personally answer all the questions which are asked here. If you are stuck anywhere, ask a question or you can message me directly and I will answer all your doubts. Are you getting updated content? Yes, I keep updating the content always to make sure, I provide all the information to my students. Once you enroll for this course, you will master these concepts in detail- 1) Selecting Records from Table - SELECT statement in SQL 2) Filtering the Records - Using WHERE clause in SQL 3) Sorting Records - Using ORDER BY clause 5) Grouping data - using GROUP BY clause 6) complete guide with examples of all the Functions - All aggregate functions covered 7) Creating simple and advanced Tables - with constraints and without constraints 8) Keys , Index - PRIMARY KEY , FOREIGN KEY , UNIQUE INDEX 9) Inserting records(loading) - with INSERT Statement 10) Updating the records of a Table - Using UPDATE statement 11) Combining multiple tables - Using UNIONS 12) Joining multiple columns of different tables - Using JOINs 13) Modify table properties - ALTER statement 14) Deleting records from the table - DELETE statement 15) Removing tables from the database permanently - DROP statement Note : This course helps to learn Microsoft SQL using Microsoft SQL Server 2019 but you can also use Microsoft SQL Server 2012, Microsoft SQL Server 2016, Microsoft SQL Server 2017, etc. It will also help to learn SQL in Oracle, MySql, PostgreSQL, Microsoft Access, SQLite, MongoDB, IBM DB2, Redis, ElasticSearch, Cassandra, Splunk, MariaDB, Teradata, Hive, Solr, HBase, FileMaker, SAP HANA, Amazon DynamoDB, SAP Adaptive Server, Neo4J, CouchBase, Memcached, and Microsft Azure SQL'.

MongoDB is a very popular open source cross-platform document-oriented database program. This comprehensive tutorial is your one-stop guide to all the aspects of MongoDB administration. You will start with jumping into the configuration, indexing and aggregation aspects of MongoDB. You’ll also see how you can optimize your query performance. Later, we’ll explore the core administration tasks such as deployment, replication, sharding, and application. This course will equip you with all the skills you need to manage a highly efficient database. About the Author Jayant Mohite has been a Big Data Consultant for the last seven years and has delivered training and support to more than 40 companies including top ones such as TCS, Synechron, PWC, SAP, HP and Vodafone. He is a trainer and consultant in his own Training & Development Platform. He has been associated with MongoDB as their official technology partner. He is also a reseller partner for IBM has worked on more than 8 projects on MongoDB. He has worked with HP as an author of Big Data Book for Micro Focus.

Mongodb is a one of the most popular NO-SQL database management system today. As against the traditional RDBMS, it stores the data in an unnormalized way, in binary JSON format. Mongodb is an open source document database. The name is derived from Hu mongo us DB . This falls into the category of NO-SQL databases. The data in Mongodb is stored in an un-normalized format, as a collection of documents. A collection in Mongodb is equivalent of a table in RDBMS and a document is equivalent of a record. However, unlike a record, a document need not have the same structure as other documents in the same collection. All the best!

In this Word2Vec tutorial , you will learn how to train a Word2Vec Python model and use it to semantically suggest names based on one or even two given names . This Word2Vec tutorial is meant to highlight the interesting, substantive parts of building a word2vec Python model with TensorFlow . Word2vec is a group of related models that are used to produce Word Embeddings . Embedding vectors created using the Word2vec algorithm have many advantages compared to earlier algorithms such as latent semantic analysis. Word embedding is one of the most popular representation of document vocabulary. It is capable of capturing context of a word in a document, semantic and syntactic similarity, relation with other words, etc. Word Embeddings are vector representations of a particular word. The best way to understand an algorithm is to implement it. So, in this course you will learn Word Embeddings by implementing it in the Python library, TensorFlow . Word2Vec is one of the most popular techniques to learn word embeddings using shallow neural network . Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. In this Word2Vec tutorial, you will learn The idea behind Word2Vec: Take a 3 layer neural network. (1 input layer + 1 hidden layer + 1 output layer) Feed it a word and train it to predict its neighbouring word. Remove the last (output layer) and keep the input and hidden layer. Now, input a word from within the vocabulary. The output given at the hidden layer is the ‘word embedding’ of the input word. In this Word2Vec tutorial we are going to do all steps of building and training a Word2vec Python model (including pre-processing, tokenizing, batching, structuring the Word2Vec Python model and of course training it) using Python TensorFlow. Finally, we are going to use our trained Word2Vec Python model to semantically suggest names based on one or even two given names. Let's start!

New! Completely updated and re-recorded for Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API. “Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark . Employers including Amazon , EBay , NASA JPL , and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think, and you'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Spark works best when using the Scala programming language, and this course includes a crash-course in Scala to get you up to speed quickly. For those more familiar with Python however, a Python version of this class is also available: "Taming Big Data with Apache Spark and Python - Hands On". Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples , and then scale them up to run on cloud computing services in this course. Learn the concepts of Spark's Resilient Distributed Datasets, DataFrames, and Datasets. Get a crash course in the Scala programming language Develop and run Spark jobs quickly using Scala, IntelliJ, and SBT Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop YARN distributes Spark across computing clusters Practice using other Spark technologies, like Spark SQL, DataFrames, DataSets, Spark Streaming, Machine Learning, and GraphX By the end of this course, you'll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most “popular" superhero is – and develop a system to find “degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to SpiderMan? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon's Elastic MapReduce service. over 8 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Enroll now, and enjoy the course! "I studied Spark for the first time using Frank's course "Apache Spark 2 with Scala - Hands On with Big Data!". It was a great starting point for me,  gaining knowledge in Scala and most importantly practical examples of Spark applications. It gave me an understanding of all the relevant Spark core concepts,  RDDs, Dataframes & Datasets, Spark Streaming, AWS EMR. Within a few months of completion, I used the knowledge gained from the course to propose in my current company to  work primarily on Spark applications. Since then I have continued to work with Spark. I would highly recommend any of Franks courses as he simplifies concepts well and his teaching manner is easy to follow and continue with!  " - Joey Faherty

In many data centers, different type of servers generate large amount of data(events, Event in this case is status of the server in the data center) in real-time. There is always a need to process these data in real-time and generate insights which will be used by the server/data center monitoring people and they have to track these server's status regularly and find the resolution in case of issues occurring, for better server stability. Since the data is huge and coming in real-time, we need to choose the right architecture with scalable storage and computation frameworks/technologies. Hence we want to build the Real Time Data Pipeline Using Apache Kafka, Apache Spark, Hadoop, PostgreSQL, Django and Flexmonster on Docker to generate insights out of this data. The Spark Project/Data Pipeline is built using Apache Spark with Scala and PySpark on Apache Hadoop Cluster which is on top of Docker. Data Visualization is built using Django Web Framework and Flexmonster.

LAST UPDATED: November 2020 (Source Code Included for Lectures) Get ready to acquire some seriously marketable programming skills! You can't consider yourself a complete end to end developer until you can code in SQL. Today, data has become the hottest topic in technology and a company's biggest asset is their data. All databases require the language SQL to store and retrieve data. Salaries for junior level SQL Developers are upwards of $70,000 - $90,000 dollars a year! The great thing is, for this course, you do not need any prior experience in programming what so ever. SQL is a different animal and we're going to demystify the language from scratch and prepare you with plenty of progressively challenging assignments so that by the time you've completed the course (in 2 months), you can call your self an Oracle SQL Master! Oracle is the most popular relational database in the world! This course will prepare you to be job-ready in just 1 month of study and practice. All exercises and solutions are in the lectures. In several lectures I ask students to pause the video and complete the assignment before resuming to watch my solution. MAKE SURE YOU WORK OUT THE PROBLEMS ON YOUR OWN BEFORE MOVING ON TO MY SOLUTION!! With over 62,000 enrolled students and a 4.5 star-rating, this is a Udemy best-selling course. Do you have no prior experience in SQL development? This course is perfect for you. Don't take it from me, take it from actual students that took this course: " I am a beginner and the way this course starts is perfect for the person who has no introduction of SQL or Oracle." Do you have prior experience, but need a refresher or to fine-tune your skills? This is the course for you. Again, I'll let my students do the talking: " I had a good base of knowledge from my last employment. This course is constantly proving useful to supercharge my actual knowledge base . Very good one! " Have you taken a SQL course before, but felt confused on certain topics or not completely satisfied in your abilities? A lot of my students had shared similar concerns: " I had previously taken a college course about databases and SQL, but these ten hours of content were more clear and useful than the course and textbook." Topics covered in this course : Basics of Tables SELECT and WHERE Clause WHERE, AND & OR with Operators BETWEEN, IN and NULL Single Table Queries Single Row Functions Grouping Functions GROUP BY and HAVING Clause Joins Inner and Outer Joins EXISTS & NOT EXIST Operators Creating Your Own Tables Using ALTER Creating Tables with SELECT & UPDATE Data DELETE, TRUNCATE, and DROP Commands System Tables, Pseudo Columns & Deleting Duplicates (Newly Added) Views and Other Objects and Commands (Newly Added)

Welcome to Natural Language Processing (NLP) Interview Test Series We have created these real-time full practice tests based on our real interview experience. With the help of these practice test you would be able to clear your NLP interview in first attempt. This is the most comprehensive Test Series online to help you ace your Data Science/Natural Language Processing interviews!

New! Updated for Spark 3, more hands-on exercises, and a stronger focus on DataFrames and Structured Streaming. “Big data" analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark . Employers including Amazon , EBay , NASA JPL , and Yahoo all use Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You'll learn those same techniques, using your own Windows system right at home. It's easier than you might think. Learn and master the art of framing data analysis problems as Spark problems through over 20 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Learn the concepts of Spark's DataFrames and Resilient Distributed Datastores Develop and run Spark jobs quickly using Python Translate complex analysis problems into iterative or multi-stage Spark scripts Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop YARN distributes Spark across computing clusters Learn about other Spark technologies, like Spark SQL, Spark Streaming, and GraphX By the end of this course, you'll be running code that analyzes gigabytes worth of information – in the cloud – in a matter of minutes. This course uses the familiar Python programming language ; if you'd rather use Scala to get the best performance out of Spark, see my "Apache Spark with Scala - Hands On with Big Data" course instead. We'll have some fun along the way. You'll get warmed up with some simple examples of using Spark to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most “popular" superhero is – and develop a system to find “degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together – both on your own system, and in the cloud using Amazon's Elastic MapReduce service. 7 hours of video content is included, with over 20 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Spark-based technologies, including Spark SQL, Spark Streaming, and GraphX. Wrangling big data with Apache Spark is an important skill in today's technical world. Enroll now! " I studied "Taming Big Data with Apache Spark and Python" with Frank Kane, and helped me build a great platform for Big Data as a Service for my company. I recommend the course!  " - Cleuton Sampaio De Melo Jr.

MongoDB makes it possible to store and process large sets of data in ways that increase business value. The flexibility of unstructured, schema-less, storage, combined with robust querying and post-processing functionality, make MongoDB a compelling solution for enterprise big data needs. We need to discuss database schemas. Yes, MongoDB is touted as schema-less but here's where we show that proper design is what allows our collections to scale. Indexing is something everyone talks about, but few understand. We'll explain MongoDB indexing, and index properties because a successful indexing strategy is a key to performance and scaling. Finally, we'll talk about CRUD commands from the MongoDB client and how to write effective queries. Taking this course will help you understand supported standards and data types in MongoDB, and best practices to design collections to scale and index them. Also, you will learn some basic CRUD commands. About the Author Micheal Shallop started programming in 1981 on a Tandy TRS-80 Model 1 and hasn't stopped since. He graduated in 1991 from Oklahoma State University with an Honors degree in Computer Science. In his career, he's coded in many programming languages and has used a variety of databases, relational and otherwise. He was the technical author of a patent awarded in 2011 for his work on real-time data collection, aggregation and forecasting in a conventional (automotive) business. He is currently working for designing and writing a back-end, event-driven, object-oriented, data-agnostic framework utilizing AMQP as the data transport vector and PHP 7.1 as the primary language. He has been programming in PHP for MongoDB since 2010 and has been the architect of several systems, mostly back-end frameworks. Micheal is interested in anything with a programming language behind it. Most recently, he has been experimenting with Arduino, programming on the Raspberry Pi, and writing a social media site in Python. He is also technically skilled in RabbitMQ, general database tech, Python, C/C++, Linux