| Audience and Prerequisites | Become Certified Python Developer About The Course
The Python developer training course is designed to help students master this programming language. The program is planned while keeping in mind the needs and requirements of both students and professionals and this is why it covers both basic and advanced level of concepts such as Hadoop streaming, machine learning and MapReduce in Python. In addition to this, the course also helps you work with the packages such as Scipy and Scikit.
Audience & Pre-Requisites
The Python training course is planned and deployed while keeping in mind the requirement of the Software developers, Business Intelligence Managers and Project Managers, ETL professionals, Big Data professionals and graduates seeking to make a career in Big Data analytics. There are no specific pre-requisites for undergoing this Python course. This training is highly beneficial for the professionals who want to make a career in Python Development.
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| Objectives | Why Take this Python Training? Python is an advanced level of language which offers much higher efficiency (almost 10 times) in comparison to the older machine languages like Java and C++. The professionals adept in Python are in high demand in the industry with a senior developer of this domain having the potential of earning as high $1,00,000 in the United States. In terms of learning, the Python is an object oriented language which can be learned faster and is comparatively easier to deploy. One major advantage of this language is its compatibility with various systems such as Windows, Linux and even Mac, which makes it highly preferred in the field of data analytics. Its demand in the Big Data Hadoop environment makes it deliver very high salaries to the professionals who have completed the Python training course.
Objective Of The Course - Know the basics and understand the significance
- Learn the installation of Python
- Get your hands on sequence and file operations
- Master the MapReduce concepts essential in Hadoop deployment
- Get an opportunity to learn expressions, looping, OOP and data types
- Work on SQLite in Python and know about functions, class defining and operations
- Learn to write and deploy Pig UDF and Hive UDF using Python
- Understand the nuances of the Python’s Machine Learning Algorithms
- Get an opportunity to work on Hadoop project real-time in Python
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| Curriculum | 1. Introduction To Python - Basic concepts of Python, understanding its general purpose along with versatility and strengths, benefits of using Python in Read & Write.
2. Python Basics and its Installation - Fundamentals of Python, its objects and data types
- Learning to install Python in different operating systems such as Windows, Linux and Mac
- Understanding Python integrated development environment and its variables.
- Run Python programming
3. Get familiar with Object oriented programming concept - Understanding the concepts of OOP, Built-in as well as user defined Python functions
- Get introduced to the Python Methods, Lists, Loops, Strings, Tuples, program flow of control
- Syntax and documentation in Python
4. Study Advanced Python - Understand different types of exception handling, handling of files in file system, learning to define a class
- Understanding API in Python database and SQLite in Python
5. Study Deployment of Python in Hadoop Environment - Master the concepts and components of Hadoop and its ecosystem.
- Understanding Hadoop Common, HDFS and MapReduce Architecture
- Learning Python scripting for MapReduce in Hadoop framework.
6. Functions & Components Of Python - Learning core concepts of Python, Introduction to the Python dictionary
- Various Python functions such as Lambda,
- Knowing the extensive Python Libraries
7. Machine Learning in Python - Learning core concepts of Python, Introduction to the Python dictionary
- Various Python functions such as Lambda functions, knowing the extensive Python Libraries, etc.
- Machine learning concepts and working of Python in machine learning set-up, supervised and unsupervised machine learning, developing machine learning algorithms, working with data and deploying Python based machine learning techniques in real world cases.
- Learning and managing Sandbox, working with HDFS and Mapping and Reducing functions in Python.
8. Project Work
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