Python: Big Data Analytics and Data Science
Python: Big Data Analytics and Data Science, available at $44.99, has an average rating of 4.1, with 8 lectures, based on 28 reviews, and has 189 subscribers.
You will learn about Tools for Big Data Analysis and Deep Learning, Tools for Handling Volume, Tools for Handling Variety, Tools for Handling Velocity, Tools for Big Data, Big Data, Data Science, Tools for Reporting and Business Intelligence, Tools for Predictive Analytics and Machine Learning, Frameworks for Deep Learning, Artificial Intelligence Tools, Installing Anaconda, Updating Anaconda, Installing Prospector Static Code Analysis Tool, Installing Jupyter-Matplotlib, Installing Packages in Anaconda, Package Managers, pip, conda Python Introduction, Why Python is popular?, Why Everyone should consider learning it, Python Standard Libraries, Data-Science Libraries, IPython Interactive Mode, Executing a Python Program Using the IPython Interpreter, Writing and Executing Code in a Jupyter Notebook, HOW BIG IS BIG DATA?, Megabytes (MB), Gigabytes (GB), Terabytes (TB), Petabytes, Exabytes and Zettabytes, Additional Big-Data Stats, Computing Power Over the Years, Data Science and Big Data Are Making a Difference: Use Cases, A Big-Data Mobile Application – Case Study, Google’s Waze GPS navigation app Introduction to Databases, Apache Hadoop, Apache Spark, IoT, Cloud and Desktop Big-Data Software, Algorithms, Data, Data’s Meaning, Big-Data Sources elational Databases, Structured Query Language, Creating and connecting to the Database, sqlite3 module, Viewing the Table’s Contents, Entity-Relationship (ER) Diagram, SELECT Queries, WHERE Clause, Pattern Matching: Zero or More Characters, Pattern Matching: Any Character, ORDER BY Clause, Sorting By Multiple Columns, Combining the WHERE and ORDER BY Clauses, Merging Data from Multiple Tables: INNER JOIN, INSERT INTO Statement, UPDATE Statement, DELETE FROM Statement, Closing the Database NoSQL, NewSQL, NoSQL Key-Value Databases, NoSQL Document Databases, NoSQL Graph Databses, NoSQL Columnar Databases, Comparison of RDBMS, NoSQL and NewSQL MongoDB JSON Document Database, pymongo, dnspython, Twitter Developer Account, Tweeter API, Creating App,Consumer API Key, API Secret Key, Access Token, Access Token Secret, Tweeter Authentication, OpenMapQuest Geocoding API, MapQuest API Key, MongoDB Atlas Cluster, Creating MongoDB Atlas Cluster, Create Database User, Whitelist IP Address, Network Access, Database Access, Connect to Cluster using Connection String, Generating Connection String, Tweepy for Authentication, Streaming Tweets into MongoDB, Loading Data from Tweeter, Configuring MongoClient, Setting up Tweet Stream, Starting Tweet Stream, TweetListener, Counting Tweets, Display Tweet Counts, Plotting Markers on Location, geopy, Creating Map, Folium Map, Creating a Choropleth, Color the Map, Creating Map Markers, Visualizing Map using folium library, Data Analytics on Big Data Apache Hadoop, Hadoop Overview, HDFS, MapReduce, YARN, Hadoop Ecosystem, Hadoop Providers, Hadoop 3, Summarizing Word Lengths in Romeo and Juliet via MapReduce, Creating an Apache Hadoop Cluster in Microsoft Azure HDInsight, Creating an HDInsight Hadoop Cluster, Hadoop Streaming, Implementing the Mapper, Implementing the Reducer,Preparing to Run the MapReduce, Copying RomeoAndJuliet into the Hadoop File System, Running the MapReduce Job, Viewing the Word Counts, Deleting Your Cluster So You Do Not Incur Charges IoT, IoT Issues, Publish and Subscribe, Visualizing a PubNub Sample Live Stream with a Freeboard Dashboard, Signing up for Freeboard io, Creating a New Dashboard, Adding a Data Source, Adding a Pane for the Humidity Sensor, Adding a Sparkline and a Gauge to the Humidity Pane, Completing the Dashboard, Simulating an Internet-Connected Thermostat in Python, Installing Dweepy, Invoking the simulator Script, Sending Dweets, Creating the Dashboard with Freeboard io, Creating a Python PubNub Subscriber This course is ideal for individuals who are Beginner Python Developers curious About Big Data Analysis, Data Science, Handling Big Data in IoT It is particularly useful for Beginner Python Developers curious About Big Data Analysis, Data Science, Handling Big Data in IoT.
Enroll now: Python: Big Data Analytics and Data Science
Summary
Title: Python: Big Data Analytics and Data Science
Price: $44.99
Average Rating: 4.1
Number of Lectures: 8
Number of Published Lectures: 8
Number of Curriculum Items: 8
Number of Published Curriculum Objects: 8
Original Price: ₹1,799
Quality Status: approved
Status: Live
What You Will Learn
- Tools for Big Data Analysis and Deep Learning, Tools for Handling Volume, Tools for Handling Variety, Tools for Handling Velocity, Tools for Big Data, Big Data, Data Science, Tools for Reporting and Business Intelligence, Tools for Predictive Analytics and Machine Learning, Frameworks for Deep Learning, Artificial Intelligence Tools, Installing Anaconda, Updating Anaconda, Installing Prospector Static Code Analysis Tool, Installing Jupyter-Matplotlib, Installing Packages in Anaconda, Package Managers, pip, conda
- Python Introduction, Why Python is popular?, Why Everyone should consider learning it, Python Standard Libraries, Data-Science Libraries, IPython Interactive Mode, Executing a Python Program Using the IPython Interpreter, Writing and Executing Code in a Jupyter Notebook, HOW BIG IS BIG DATA?, Megabytes (MB), Gigabytes (GB), Terabytes (TB), Petabytes, Exabytes and Zettabytes, Additional Big-Data Stats, Computing Power Over the Years, Data Science and Big Data Are Making a Difference: Use Cases, A Big-Data Mobile Application – Case Study, Google’s Waze GPS navigation app
- Introduction to Databases, Apache Hadoop, Apache Spark, IoT, Cloud and Desktop Big-Data Software, Algorithms, Data, Data’s Meaning, Big-Data Sources
- elational Databases, Structured Query Language, Creating and connecting to the Database, sqlite3 module, Viewing the Table’s Contents, Entity-Relationship (ER) Diagram, SELECT Queries, WHERE Clause, Pattern Matching: Zero or More Characters, Pattern Matching: Any Character, ORDER BY Clause, Sorting By Multiple Columns, Combining the WHERE and ORDER BY Clauses, Merging Data from Multiple Tables: INNER JOIN, INSERT INTO Statement, UPDATE Statement, DELETE FROM Statement, Closing the Database
- NoSQL, NewSQL, NoSQL Key-Value Databases, NoSQL Document Databases, NoSQL Graph Databses, NoSQL Columnar Databases, Comparison of RDBMS, NoSQL and NewSQL
- MongoDB JSON Document Database, pymongo, dnspython, Twitter Developer Account, Tweeter API, Creating App,Consumer API Key, API Secret Key, Access Token, Access Token Secret, Tweeter Authentication, OpenMapQuest Geocoding API, MapQuest API Key, MongoDB Atlas Cluster, Creating MongoDB Atlas Cluster, Create Database User, Whitelist IP Address, Network Access, Database Access, Connect to Cluster using Connection String, Generating Connection String, Tweepy for Authentication, Streaming Tweets into MongoDB, Loading Data from Tweeter, Configuring MongoClient, Setting up Tweet Stream, Starting Tweet Stream, TweetListener, Counting Tweets, Display Tweet Counts, Plotting Markers on Location, geopy, Creating Map, Folium Map, Creating a Choropleth, Color the Map, Creating Map Markers, Visualizing Map using folium library, Data Analytics on Big Data
- Apache Hadoop, Hadoop Overview, HDFS, MapReduce, YARN, Hadoop Ecosystem, Hadoop Providers, Hadoop 3, Summarizing Word Lengths in Romeo and Juliet via MapReduce, Creating an Apache Hadoop Cluster in Microsoft Azure HDInsight, Creating an HDInsight Hadoop Cluster, Hadoop Streaming, Implementing the Mapper, Implementing the Reducer,Preparing to Run the MapReduce, Copying RomeoAndJuliet into the Hadoop File System, Running the MapReduce Job, Viewing the Word Counts, Deleting Your Cluster So You Do Not Incur Charges
- IoT, IoT Issues, Publish and Subscribe, Visualizing a PubNub Sample Live Stream with a Freeboard Dashboard, Signing up for Freeboard io, Creating a New Dashboard, Adding a Data Source, Adding a Pane for the Humidity Sensor, Adding a Sparkline and a Gauge to the Humidity Pane, Completing the Dashboard, Simulating an Internet-Connected Thermostat in Python, Installing Dweepy, Invoking the simulator Script, Sending Dweets, Creating the Dashboard with Freeboard io, Creating a Python PubNub Subscriber
Who Should Attend
- Beginner Python Developers curious About Big Data Analysis, Data Science, Handling Big Data in IoT
Target Audiences
- Beginner Python Developers curious About Big Data Analysis, Data Science, Handling Big Data in IoT
This course covers following contents in depth
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Tools for Big Data Analysis and Deep Learning
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Python Introduction Why Python is popular?
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Python Libraries for handling Big Data Exploration and Visualization
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Introduction to Databases, Apache Hadoop, Apache Spark, IoT
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Relational Databases
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NoSQL, NewSQL Databases
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MongoDB JSON Document Database
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Microsoft Azure HD Insight
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Tweeter API
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Apache Hadoop, HDFS, MapReduce, YARN
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IoT, IoT Issues, Publish and Subscribe Model
This course will be beneficial for the learners we want to start their journey in Big Data domain. They can acquire jobs like Azure Developer, Data Analyst, Data Architect, Cluster Administrator, etc.
Course Curriculum
Chapter 1: Session 1: Big Data Analytics and Data Science with Python
Lecture 1: Tools for Big Data Analysis, Data Science, Machine Learning and Deep Learning
Chapter 2: Session 2: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 2: Python and Big Data Introduction
Chapter 3: Session 3: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 3: Introduction to Databases
Lecture 2: Lecture 4: Relational Databases and sqlite3
Chapter 4: Session 4: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 5: Types of Big Databases
Chapter 5: Session 5: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 6: MongoDB, Twitter API, OpenMapQuest, Folium Map
Chapter 6: Session 6: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 7: Apache Hadoop, Microsoft Azure HDInsight and MapReduce
Chapter 7: Session 7: Big Data Analytics and Data Science with Python
Lecture 1: Lecture 8: Big Data in IoT
Instructors
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Dr Amol Prakash Bhagat
Researcher and Innovator
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 4 votes
- 3 stars: 5 votes
- 4 stars: 9 votes
- 5 stars: 10 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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