Python Courses in Dubai

Course Details

ABOUT THE COURSE

Data science doesn’t need to be the complex subject it is thought to be. Not with Simpliv, for sure. Understand when to use the right tools, how to connect to the right data source, how to connect Tableau Desktop with R to optimize the functions of R, packages, libraries and saved models. Also, learn to use Python scripts for your fields in Tableau in the same way as you do with R. Ideal for becoming a complete data professional.

Who is the target audience?

 All the professionals who are passionate about business intelligence, data visualization, and data analytics.Basic knowledge:

 There are no prerequisites for taking up this certification training course.

Curriculum

Visualization with Tableau

• Tableau - An Introduction   
• Aggregation and Granularity   
• Action Filters and Action Highlights   
• Customer Segmentation Dashboard   
• Data Blending   
• Find top 10 Gems   
• Table Calculations (Explaining various Table calculations )   
• Difference between Table calculations and Calculated fields  
• LOD Functions   
• How to connect to databases (Video-based)   
• How to integrate Tableau with R (Video-based)   
• Dashboarding Techniques   
• Other Charts   

Python and R basics

• Tableau - An Introduction   
• Core programming concepts   
• Objects in Python   
• Visualizations in Python  
• Packages in Python   
• Packages in Python   
• Matrix Operations  
• Data frames   
• Introduction to R   
• Objects in R   
• Core programming concepts   
• Visualizations in R (Packages in R)   
• Matrix Operations  
• Data frames   
• Lists in R  
• Apply family functions in R  
• Projects and Tests  

Price:  Ã¢â€šÂ¹ 16665 (Enroll Today and Get Flat 40% OFF)

New Batch starts from 21ST Jan 2019 Days: Mon-Fri (15 Days) 07:00 PM - 10:00 PM (IST)

Course Details

See why over 350,000 Simpliv members learn coding from Mark Lassoff and LearnToProgram.tv!

Few programming languages provide you with the flexibility and pure power of Python.

If you're becoming a professional developer, or are early in your development career, adding the Python skill set isn't just a resume embellishment-- It's an empowering language that will allow you to write procedural code in many types of environments and for many uses.

Python is commonly used for server-side programming for complex web applications or as a middle tier language providing web services or a communication layer with larger e-commerce systems. That being said, it's also a great language for beginners. The clear syntax makes it very easy to learn, and the powerful libraries make all types of programming possible. There are libraries for everything from games and graphics to complex mathematics to network and embedded programming.

Watch, Learn and Do

Programming is not a spectator sport and if you want to learn Python well, this course contains everything you need.

Skill oriented instructor-led lectures will demonstrate each important Python skill. You'll be able to study and modify the code on your own to cement each topic. Python code coding lab exercises will familiarize you not just with Python syntax, but how real problem-solving in Python is done. You'll complete a more comprehensive project to help you integrate the different skills that are part of core Python.

Who is the target audience?

• First time Python programmers
• Students and Teachers
• IT pros who want to learn to code
• Aspiring data scientists who want to add Python to their tool arsenal

BASIC KNOWLEDGE

• Students should be comfortable working in the PC or Mac operating system

WHAT YOU WILL LEARN

• How to use the Python Shell
• How to use interactive mode in Python
• How to develop and run programs in the IDLE editor
• How to run Python scripts directly from the command line
• How to use the print() function
• How to use separators and new line characters to modify command line output
• Assign variables of different types
• Understand integer, floating point, complex and string variables
• Be able to extract substrings
• Easily concatenate strings
• Create Lists and Tuples
• Create key value pairs and store them in dictionaries
• Understand mathematical operators used in Python
• Apply the order of operations to mathematical operations
• Utilize comparison operators to determine logical outcomes
• Use logical operators to join comparisons
• Write conditional statements to correctly branch code
• Use If, else and else if statements to apply branching
• Understand how and when to used nested if statements
• Use the shortcut Ternary operator
• Be able to use looping structures effectively
• Create While loops
• Be able to use For loops to loop through an objects properties
• Be able to construct nested loops and understand their utility.
• Cast variables from one type to another using built-in Python functions
• Use the Mathematical functions within Python to evaluate expressions
• Randomize numbers and selections with the Randomization tools
• Use Python String functions such as find(), join() and split()
• Create immutable tuples
• Access values within tuples
• Use tuple functions to manipulate tuple data
• Declare a dictionary and populate it with key/value pairs
• Access and edit values within dictionaries
• Extract date and time information from the time tuple
• Use the calendar object to work with calendar related information
• Create custom functions
• Send arguments to functions using order or keyword
• Create default function arguments
• Read and obtain keyboard input
• Read from a text file and process the data in Python
• Write to a text file from Python
• Append to a text file
• Handle exceptions with try/except/else in Python
• Use Python within the cgi-bin or a web server
• Process form data from Python

Course Details

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. 

Get your data to fly using Spark for analytics, machine learning and data science 

Let’s parse that.

What's Spark? If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.

Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease. 

Machine Learning and Data Science : Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets. 

What's Covered:

Lot's of cool stuff ..

• Music Recommendations using Alternating Least Squares and the Audioscrobbler dataset
• Dataframes and Spark SQL to work with Twitter data
• Using the PageRank algorithm with Google web graph dataset
• Using Spark Streaming for stream processing 
• Working with graph data using the  Marvel Social network dataset 

.. and of course all the Spark basic and advanced features: 

• Resilient Distributed Datasets, Transformations (map, filter, flatMap), Actions (reduce, aggregate) 
• Pair RDDs , reduceByKey, combineByKey 
• Broadcast and Accumulator variables 
• Spark for MapReduce 
• The Java API for Spark 
• Spark SQL, Spark Streaming, MLlib and GraphFrames (GraphX for Python) 

Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

• Yep! Analysts who want to leverage Spark for analyzing interesting datasets
• Yep! Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it.
• Yep! Engineers who want to use a distributed computing engine for batch or stream processing or both

BASIC KNOWLEDGE

• The course assumes knowledge of Python. You can write Python code directly in the PySpark shell. If you already have IPython Notebook installed, we'll show you how to configure it for Spark
• For the Java section, we assume basic knowledge of Java. An IDE which supports Maven, like IntelliJ IDEA/Eclipse would be helpful
• All examples work with or without Hadoop. If you would like to use Spark with Hadoop, you'll need to have Hadoop installed (either in pseudo-distributed or cluster mode).

WHAT YOU WILL LEARN

• Use Spark for a variety of analytics and Machine Learning tasks
• Implement complex algorithms like PageRank or Music Recommendations
• Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
• Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX

Course Details

This course is intended to familiarize students with Python programming language and its basic constructs. 

It requires 10 hours of training split into multiple days based on student's convenience and pace.

Course Details

Join us at our Python Diploma Course in Dubai, where we equip students with the tools they need to succeed in today’s rapidly evolving programming industry. This program is flexible enough to meet the needs of both complete novices and seasoned programmers who want to learn Python.

Course Details

Coding is always fun to learn. This course will teach your child the fundamental of coding in a very easy and productive manner. The course is designed for overall development of the kid. In 8 sessions your child will learn about animation , creating games, stories creation and App development which will be highly beneficial as in the future everything is going to be dependant on coding and computers.

The course is designed to be extremely fun and interactive so all the concepts taught are absorbed organically rather than being crammed.

By the end of the course your child will have sound knowledge on the basics of programming language which will put him/her light years ahead of everyone in his/her age bracket

Upon completion of the course your child will be given a certificate by the KHDA which will help him in his future endeavours.

Course Details

Python Programming - Data Sciences Introduction to NumPy Understanding Data Types in Python Arrays in Python Fixed Type Arrays NumPy Standard Data Types Basics of NumPy Arrays NumPy Array Attribute Array Indexing and Slicing Fancy Indexing Reshaping Array Array Concatenation and Splitting Aggregation on Arrays Comparisons, Masks, and Boolean Logic on Arrays Sorting Arrays Computation on NumPy Arrays: Universal Function Data Manipulation with Pandas Introduction to Pandas Objects The Pandas Series Objects The Pandas DataFrame Objects The Pandas Index Objects Data Indexing and Selection Data Selection in series Data Selection in DataFrame Operating on Data in Pandas Ufuncs: Index Preservation Ufuncs: Index Alignment Ufuncs: Operation between DataFrame and Series Operating Null Values Hierarchical Indexing A Multiply Indexed Series Methods of MultiIndex Creation Indexing and Slicing a MultiIndex Rearranging Multi-Indices Combining Datasets: Concat and Append Combining Datasets: Merge and join Aggregation and Grouping Vectorized String Operators Working with Time Series High Performance Pandas: eval() and query() Visualization with Matplotlib Importing Matplotlib Setting styles Simple Line Plots Simple Scatter Plots Visualizing Error Density and Contour Plots Histograms, Binning and Density Customizing Plot Legends Customizing Colorbars Multiple Subplots Text and Annotation Customizing Ticks

Course Details

Course Details

This program will build upon the skills acquired in the previous module by learning and covering advanced programming concepts of web development and the Django framework.

Learning Outcomes:

• Designing the website with core concepts.
• Hosting and publishing concepts.
• Domain and server.
• Understand the core concepts of Python programming language.
• Database and SQL queries.
• Errors and exception handling.
• Implement Python structures such as if statements, loops, and functions
• Understand Python language basics and how they apply to data science.
• Read and write external data files and pickling using Python.
• Analyze data using Python libraries like pandas and SQL.
• Implementation of the Django framework.
• Advanced Python modules.

Course Details

Course Details

This program covers the fundamental programming concepts to help you understand the Python programming language.

Learning Outcomes:

• Basic as well as core concepts of Python programming language
• Implement basic Python structures such as if statements, loops, and functions
• Decorators and generators
• Comparison operators
• Data structures
• Errors and exception handling
• Python statements
• Read and write external data files using Python
• Modules and packages
• Methods and functions
• Object-oriented programming

Course Details

Course Overview

Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. This Python for beginners training course leads the students from the basics of writing and running Python scripts to more advanced features. The concepts are reinforced by practice during the lecture and then followed by lab exercises. This Python Programming Level 1 course is a practical introduction to a working programming language, not an academic overview of syntax and grammar. After completing this course students will immediately be able to use Python to complete tasks in the real world scenarios.

What will you achieve? 

Upon the completion of this course, learner will be able to

• Understand the basic as well as core concepts of Python programming language
• Implement basic Python structures such as if statements, loops, and functions
• Work with Comparison operators
• Knowledge in Decorators and generators
• Work with Data structures
• Python statements
• Handle Errors and exceptions
• Read and write external data files using Python
• Implement Methods and functions
• Using Modules and packages
• Object-oriented programming

To whom is the course for?

• Students are new to the Python language who already have experience with other programming languages.

·       Professionals

Pre-requisite: 

This course is not intended for absolute beginners in programming but includes a review of elementary features. Students are expected to be able to open a command prompt window or terminal window, edit a text file, download and install software, and understand basic programming concepts.

Course Details

Python Certification Training course teach high level programming language, the python platform handle multiple programming paradigms including object oriented, numeric datatypes, string operations, control flow and syntax, for loop, sys,math,time modules,regular expression,etc python is scripting such as language Ruby, PHP and this programming language are using for Business analytics, Artificial Intelligent, Machine learning and much more.

Who needs the Python Certification Program?

Python certification Training course will significantly useful for website development, mobile app development, ERP system development, desktop application building, programming professionals, and anyone who is concerned about the integrity of the Software and programming Development.

Course Details

About this Course

This course introduces Python programming as a way to have hands-on experience with Data Science. It starts with a few basic examples in Python before moving onto doing statistical processing. The course then introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.

Basic knowledge

• This course is for beginners, but it helps to have some basic understanding of statistics (mean, median, scatter plot) and preliminary knowledge of any programming. The course also assumes that you know how to download and install various programs/apps, and you are able to edit and debug simple programs

What you will learn

• Writing simple Python scripts to do basic mathematical and logical operations
• Loading structured data in a Python environment for processing
• Creating descriptive statistics and visualizations
• Finding correlations among numerical variables
• Using regression analysis to predict the value of a continuous variable
• Building classification models to organize data into pre-determined classes
• Organizing given data into meaningful clusters
• Applying basic machine learning techniques for solving various data problems

Course Details

Specialities of our course:

• Convenient Payment System
• ISO 9001-2008 Certified Center
• Free Car Parking
• 25 Certified Trainers
• Special attention to students and corporate people

Course Details

Specialities of our course:

• Convenient Payment System
• ISO 9001-2008 Certified Center
• Free Car Parking
• 25 Certified Trainers
• Special attention to students and corporate people

Course Details

Course Outline:

• Introduction
• Learning to Program
• Calculations and Variables
• Strings, Lists, Tuples, and Maps
• Drawing with Turtles
• Asking Questions with if and else
• Going Loopy
• Recycling Your Code with Functions and Modules
• How to Use Classes and Objects
• Python’s Built-In Functions
• Useful Python Modules
• More Turtle Graphics
• Using tkinter for Better Graphics
• Beginning Your First Game: Bounce!

Course Details

Topics covered:

• Modules and Libraries
• Text I/O Handling
• Python Integration Primer
• Introduction to Python
• Working with Data
• Program Organization and Functions
• Classes and Objects
• Inside the Python Object System
• Testing, Debugging, and Software Development Practice
• Iterators and Generators
• Some Advanced Topics

Course Details

Course details:

1. Your First Web Scraper

2. Advanced HTML Parsing

3. Starting to Crawl

4. Using APIs

5. Storing Data

6. Reading Documents

7. Cleaning Your Dirty Data

8. Reading and Writing Natural Languages

9. Crawling Through Forms and Logins

10. Scraping JavaScript

11. Image Processing and Text Recognition

12. Avoiding Scraping Traps

13. Testing Your Website with Scrapers

Course Details

Python course helps in Data Science courses. Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. We specialise in offering Python classroom training.

Topics covered:

1. Introduction to Python Training in Bangalore

2. Python Environment

3. Executing Python

4. Python Basic Syntax

5. Python Variable Types

6. Python Basic Operators

7.Python Decision Making

8. Python Loops

9. Python Numbers

10. Python Strings

11. Python Lists

12. Python Tuples

13. Python Dictionary

14. Python Functions

15. Python Modules

16. Python Files I/O

17. Python Exceptions

18. Python Classes and Objects

19. Python Regular Expressions

20. XML/JSON processing

21. Functional Programming

22. Advanced Concepts

Course Details

Course content:

1. Introduction to Python Programming Language

2. Data Collections and Language Component

3. Object and Classes

4. Functions and Modules

5. I/O and Error Handling In Python

6. Functions

7. Modules

8. Execution Environment

9. Regular Expressions

10. Network Programming

11. Multithreaded Programming

12. GUI Programming with Tkinter

13. Web Programming

14. Extending Python

Course Details

•  Python review
•  Classes and Objects
•  Advanced I/O Handling
•  Idiomatic Data Handling
•  Inside the Python Object Model
•  Testing, Debugging and Logging
•  Packages and Distribution
•  Iterators, Generators, Coroutines
•  Functional Programming
•  Metaprogramming
•  Extension Programming
•  Concurrent Programming with Threads
•  Multiprocessing
•  Python 3

Course Details

Few programming languages provide you with the flexibility and pure power of Python.

If you're becoming a professional developer, or are early in your development career, adding the Python skill set isn't just a resume embellishment-- It's an empowering language that will allow you to write procedural code in many types of environments and for many uses.

Python is commonly used for server side programming for complex web applications or as a middle tier language providing web services or a communication layer with larger ecommerce systems. That being said, it's also a great language for beginners. The clear syntax makes it very easy to learn, and the powerful libraries make all types of programming possible. There are libraries for everything from games and graphics to complex mathematics to network and embedded programming.

Watch, Learn and Do

Programming is not a spectator sport and if you want to learn Python well, this course contains everything you need.

Skill oriented instructor-led lectures will demonstrate each important Python skill. You'll be able to study and modify the code on your own to cement each topic. Python code coding lab exercises will familiarize you not just with Python syntax, but how real problem-solving in Python is done. You'll complete a more comprehensive project to help you integrate the different skills that are part of core Python.

Who is the target audience?

• First time Python programmers
• Students and Teachers
• IT pros who want to learn to code
• Aspiring data scientists who want to add Python to their tool arsenal

BASIC KNOWLEDGE

• Students should be comfortable working in the PC or Mac operating system

WHAT YOU WILL LEARN

• How to use the Python Shell
• How to use interactive mode in Python
• How to develop and run programs in the IDLE editor
• How to run Python scripts directly from the command line
• How to use the print() function
• How to use separators and new line characters to modify command line output
• Assign variables of different types
• Understand integer, floating point, complex and string variables
• Be able to extract substrings
• Easily concatenate strings
• Create Lists and Tuples
• Create key value pairs and store them in dictionaries
• Understand mathematical operators used in Python
• Apply the order of operations to mathematical operations
• Utilize comparison operators to determine logical outcomes
• Use logical operators to join comparisons
• Write conditional statements to correctly branch code
• Use If, else and else if statements to apply branching
• Understand how and when to used nested if statements
• Use the shortcut Ternary operator
• Be able to use looping structures effectively
• Create While loops
• Be able to use For loops to loop through an objects properties
• Be able to construct nested loops and understand their utility.
• Cast variables from one type to another using built-in Python functions
• Use the Mathematical functions within Python to evaluate expressions
• Randomize numbers and selections with the Randomization tools
• Use Python String functions such as find(), join() and split()
• Create immutable tuples
• Access values within tuples
• Use tuple functions to manipulate tuple data
• Declare a dictionary and populate it with key/value pairs
• Access and edit values within dictionaries
• Extract date and time information from the time tuple
• Use the calendar object to work with calendar related information
• Create custom functions
• Send arguments to functions using order or keyword
• Create default function arguments
• Read and obtain keyboard input
• Read from a text file and process the data in Python
• Write to a text file from Python
• Append to a text file
• Handle exceptions with try/except/else in Python
• Use Python within the cgi-bin or a web server
• Process form data from Python

Course Details

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data. 

Get your data to fly using Spark for analytics, machine learning and data science 

Let’s parse that.

What's Spark? If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.

Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease. 

Machine Learning and Data Science : Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets. 

What's Covered:

Lot's of cool stuff ..

• Music Recommendations using Alternating Least Squares and the Audioscrobbler dataset
• Dataframes and Spark SQL to work with Twitter data
• Using the PageRank algorithm with Google web graph dataset
• Using Spark Streaming for stream processing 
• Working with graph data using the  Marvel Social network dataset 

.. and of course all the Spark basic and advanced features: 

• Resilient Distributed Datasets, Transformations (map, filter, flatMap), Actions (reduce, aggregate) 
• Pair RDDs , reduceByKey, combineByKey 
• Broadcast and Accumulator variables 
• Spark for MapReduce 
• The Java API for Spark 
• Spark SQL, Spark Streaming, MLlib and GraphFrames (GraphX for Python) 

Using discussion forums

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We're super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

• Yep! Analysts who want to leverage Spark for analyzing interesting datasets
• Yep! Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it.
• Yep! Engineers who want to use a distributed computing engine for batch or stream processing or both

BASIC KNOWLEDGE

• The course assumes knowledge of Python. You can write Python code directly in the PySpark shell. If you already have IPython Notebook installed, we'll show you how to configure it for Spark
• For the Java section, we assume basic knowledge of Java. An IDE which supports Maven, like IntelliJ IDEA/Eclipse would be helpful
• All examples work with or without Hadoop. If you would like to use Spark with Hadoop, you'll need to have Hadoop installed (either in pseudo-distributed or cluster mode).

WHAT YOU WILL LEARN

• Use Spark for a variety of analytics and Machine Learning tasks
• Implement complex algorithms like PageRank or Music Recommendations
• Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
• Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX

Course Details

This course, designed for professional software developers, scientists, and engineers, is a comprehensive introduction to the Python programming language, standard library, and Python programming techniques. Although the course assumes no prior experience with Python, the course is strongly focused on practical applications including scripting, data processing, systems administration, and integrating Python with other software.