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New Age Online Python Training & Certification

Get comprehensive Python training that will help you to learn the Python fundamental skills, OOPs concepts, best practices for programming, python libraries to improve your coding skills, and more that will further help you to take your career ahead in the programming space.

Next Class Begins in 8 days - 15 Dec 2019

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Why Online Python Certification?

Get advanced level Python training that can shape your career in a dynamic field of Python. Take a quick look at some of the compelling facts that make Python certification so popular these days.

#1

Career option in the programming field

$74K+

An Average salary taken by skilled entry-level Python Programmer

Python Growth

67%

Increase in jobs that demands Python skills

43K+

Jobs are posted on different job portals for skilled Python experts as per indeed.com

47%

Increase in demand for Python specialists.

Dive deep into the Python Career

Learn about Career benefits, in-demand skills, average salaries and tips to Crack Job Interview.

Python Jobs

$30

Hourly rate is taken by a Python expert as a Freelancer.

Instructor-led Live Online Classes – Python Certification


Upcoming Python Classes

Starting
Duration
Price
15 Dec

15 Dec ( 6 Weeks)

09:00 PM - 10:30 PM EST

USD 1199
Discount on Call
25 Dec

25 Dec ( 6 Weeks)

09:00 PM - 10:30 PM EST

USD 1199
04 Jan

04 Jan ( 6 Weeks)

09:00 PM - 10:30 PM EST

USD 1199
14 Jan

14 Jan ( 6 Weeks)

09:00 PM - 10:30 PM EST

USD 1199
Detail

15 Dec ( 6 Weeks)

09.00 - 10.00 PM EST

USD 1199
Discount on Call

25 Dec ( 6 Weeks)

09.00 - 10.00 PM EST

USD 1199

04 Jan ( 6 Weeks)

09.00 - 10.00 PM EST

USD 1199

Earn your Python Certificate

Best-in-class content by leading faculty & industry leaders in the form of videos and projects, assignments & live sessions.

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Python Training Course Roadmap

Here are the milestones that you will achieve with our Python Course Training

Introduction to Python

    • What is Python?
    • Python History
    • Python Benefits
    • Python Versions
    • Python Installation
    • Python Program execution
    • How to write your first program in Python?
    • Discuss Python Scripts on UNIX/Windows
    • Python keywords and Identifiers
    • Python statements & indentation
    • Comments in python
    • Command-line arguments

Variables, data types, Loops & Functions

    • Introduction to Variables & Data types
    • Introduction to Numbers & Strings
    • Lists, tuples & Dictionary
    • Decision making & Loops
    • Control Flow & Syntax
    • The if Statement
    • Python Operators
    • The while Loop
    • break and continue
    • For Loop
    • Pass Statement
    • Functions
    • Calling a function
    • Function arguments
    • Built-in functions
    • Scope of variables
    • Decorators
    • Passing parameters to a Function
    • Lambda
    • Closures

Modules and Packages, File Handling & Exception Handling

    • About Modules
    • Importing module
    • Standard Module - sys & OS
    • The “dir” Function
    • Packages
    • What is the data and Information File?
    • Different Modes of a File and Object Attributes
    • Creation of a File and appending data to a file.
    • Renaming and Deleting Files
    • Directories in Python
    • Working with CSV files and CSV Module
    • Common Runtime Errors in PYTHON
    • Errors & Run-Time Errors
    • Handling IO Exceptions
    • Try.... except statement

Python Class and Objects

    • Introduction to OOPs Programming
    • Classes and Objects creation
    • Class variables and Instance Variables Constructors
    • Access Modifiers
    • Defining Python classes
    • Python Namespace
    • Self-variable in python
    • Garbage Collection
    • What is Inheritance? Types of Inheritance?
    • How does Inheritance work?
    • Python Multiple Inheritance
    • Overloading and Over Riding
    • Polymorphism, Abstraction & Encapsulation

Regular expression & Multithreading

    • What is a regular expression?
    • Wild card characters
    • Forming regular expressions
    • Character classes
    • Quantifiers
    • Greedy matches
    • Grouping
    • Match and Search functions
    • Matching vs searching
    • Subfunction
    • Splitting a string
    • Replacing text
    • Defining & Starting a thread
    • Threading module
    • Threads Synchronization
    • Multithreaded Priority Queue

Python with Machine Learning & Data Analytics

    • About Machine learning
    • Machine Learning Methods
    • Predictive & Descriptive Models
    • Step-by-step guide in Machine Learning?
    • About Deep Learning
    • What are Classification and its use cases?
    • Decision Tree
    • Algorithm for Decision Tree Induction
    • Creating a Perfect Decision Tree
    • Naïve Bayes and its working
    • Implementing Naïve Bayes Classifier
    • Support Vector Machine
    • Introduction to data Big Data
    • Introduction to NumPY and SciPY
    • Introduction to Pandas and MatPlotLi

Python Training Course Roadmap

  • Here are the milestones that you will achieve with our Python Course Training

    With our completely specialized curriculum of the Python training course, hundreds of students have qualified Python certification over the past seven years and are placed with some of the leading corporations. Python is the most sought-after skill today, and the demand is sure to increase further. Expert estimates future demand for Python skills to stay exponential for at least the next 20 years.

    Here is what we cover in our online Python Course to make you a Python Expert. Each topic has been detailed with the sub-topic that we cover.

    • What is Python?
    • Why Python?
    • Who Uses Python?
    • Python Characteristics
    • Python History
    • What is PSF?
    • Python Versions
    • How to Download and Install Python?
    • Install Python with Diff IDEs
    • Features and Limitations of Python
    • Python Applications
    • Creating Your First Python Program
    • What is Variable?
    • Variables and Constants in Python
    • Variable, Variable names and Value
    • Mnemonic Variable Names
    • Values and Types
    • Python different numerical types
    • Standard Data Types
    • Order of Operations
    • Swap variables
    • Python Mathematics
    • Type Conversion
    • Mutable Versus Immutable Objects
    • Arithmetic operators
    • Relational operators
    • Logical operators
    • Assignment operators
    • Bitwise operators
    • Membership operators
    • Identity operators
    • Ternary Operator
    • What is a string?
    • Define a string - Multiple
    • Basic String Operations
    • quotes and Multiple lines
    • String functions
    • String slicing - start, end & step
    • String operations and indices
    • String Functions, Methods
    • Delete a string
    • String Multiplication and concatenation
    • Python Keywords, Identifiers, and Literals
    • String Formatting Operator
    • Structuring with Indentation in Python
    • How to use “if condition” in conditional structures
    • if statement (One-Way Decisions)
    • if, else statement (Two-way Decisions)
    • How to use “else condition”
    • If, else if…else statement (Multi-way)
    • When “else condition” does not work?
    • How to use the “elif” condition?
    • How to execute a conditional statement with minimal code?
    • Nested IF Statement
    • How to use “While Loop” and “For Loop”
    • How to use For Loop for a set of other things besides numbers
    • Break statements, continue statement, Enumerate function for “For” Loop
    • How to use for loop to repeat the same statement over and again
    • Break, continue statements
    • Purpose of a function
    • Defining a function
    • Calling a function
    • Function parameter passing
    • Formal arguments
    • Actual arguments
    • Positional arguments
    • Keyword arguments
    • Variable arguments
    • Variable keyword arguments
    • Use-Case *args, **kwargs
    • Function call stack
    • locals()
    • globals()
    • Stackframe
    • What is Regular Expression?
    • Regular Expression Syntax
    • Understanding Regular Expressions
    • Regular Expression Patterns
    • Literal characters
    • Repetition Cases
    • Using regular expression methods
    • Using re.match()
    • Finding Pattern in Text (re.search())
    • Using re.findall for text
    • Python Flags
    • Methods of Regular Expressions
    • Introduction to List
    • Purpose of a List
    • Iterating through a List
    • List slicing, -ve indexing
    • Internals of list
    • List Operations
    • Searching for an element
    • In and count()
    • Adding an element
    • 1) append()
    • 2) insert()
    • Removing an element
    • 1)remove()
    • pop()
    • Merging two lists
    • + operator
    • extend()
    • Advantages of Tuple over List
    • Packing and Unpacking
    • Comparing tuples
    • Creating nested tuple
    • Using tuples as keys in dictionaries
    • Deleting Tuples
    • Slicing of Tuple
    • Tuple Membership Test
    • Built-in functions with Tuple
    • Dotted Charts
    • How to create a set?
    • Iteration Over Sets
    • Python Set Methods
    • Python Set Operations
    • Union of sets
    • Built-in Functions with Set
    • Python Frozen set
    • How to create a dictionary?
    • PYTHON HASHING
    • Python Dictionary Methods
    • Copying dictionary
    • Updating Dictionary
    • Delete Keys from the dictionary
    • Dictionary items () Method
    • Sorting the Dictionary
    • Python Dictionary in-built Functions
    • Dictionary len() Method
    • Variable Types
    • Python List cmp() Method
    • Dictionary Str(dict)
    • What is a Module?
    • Types of Modules
    • The import Statement
    • The from…import Statement
    • ..import * Statement
    • Underscores in Python
    • The dir( ) Function
    • Creating User-defined Modules
    • Command-line Arguments
    • Python Module Search Path
    • What is a Package?
    • Introduction to Packages?
    • py file
    • Importing module from a package
    • Creating a Package
    • Creating Sub Package
    • Importing from Sub-Packages
    • Popular Python Packages
    • What is the data and Information File?
    • File Objects
    • Different Modes of a and Object Attributes
    • Creating, appending, and reading a File
    • Closing a file
    • Read, read a line, read lines, write, write lines
    • Renaming and Deleting Files
    • Directories in Python
    • Working with CSV files and CSV Module
    • Handling IO Exceptions

Course Curriculum

Learn what you'll get after successful enrollment

Python Corporate Training

Python Online Corporate Training & Certification

Being the most popular Programming Language, the Python Corporate Training will help your workforce to build a strong foundation and gain hands-on experience in building and deploying python-based web apps.

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"We ensure that you learn Python completely, and not only become Python Certified but also get ready for Python Job Interviews."

Our Reviews


6K + Learners | 1605 Reviews

Customer Reviews

Donny Papic

This course was amazing. Great way to learn some of the practical elements of data science. Coming from a maths background I really appreciated the fact that the theory behind the models we built was explained. A wonderful course and I am now about to enroll in other courses.

Jeffrey

This is a pretty good beginner course for anyone totally new to this field. Still, this course is a subset of Machine Learning A-Z course by the same team. Almost everything covered in this course is covered in that plus it is Hands-On in Python and R. This course basically provides a whole workflow of a data science project.

Chenaj Teja Potu

An absolutely great course. I'm new to learning about Data Science and Kirill's explanation really is step-by-step and makes no assumptions about what you should know. He explains why each action is done and how it applies to the real world. By the time you finish this course, you'll really feel much more capable of analyzing data.

Bosun Sogeke

Really this course is very helpful and I have learned a lot of new areas in data science especially data preparation, data cleaning and data analysis. I have learned about data modeling using logistic regression which will be very helpful in my day to day work.

Kim Adams

Well-structured and practice-oriented course, I would recommend it to anyone who wants to quickly get up to speed in such core Data Science skills as data visualization, ETL, modeling, and communication.

Gururaju BM

Loved this course. Lots of good material and the instructor is great. He keeps things exciting and keeps challenging. This course kind of made me realize what I like the most and pushed me towards a career path. Definitely, recommend it if you are anything like me- a fresher with little knowledge in data science and interested in pursuing a career in this field.

Nibha Thakur

I think the course did well in terms of the flow of topics and covering the fundamentals. It does add great value to beginners. However, I expected it to cover data mining and visualizations in more detail. Anyway, kudos to super data science team for their efforts.

Debmalya Datta

Very good course, love the outline of a broad topic which still has lots of practical examples. The speed is exactly right for a beginner, he doesn't dwell too long on any subject or details but instead is focused on necessary practicalities. Good job!

Prakash Shekade

This is a good survey course that has helped me not only develop the skills necessary to break into the data science field but also to understand how the entire process works as a whole. A big thank you to the JanBask team.

Buddhadev Choudhury

This is an amazing course. Probably the best introduction possible to data science. The instructor is speaking in a very understandable way and spend time on the useful details. Thanks.

Zakaria

Very good course. Gave me the information and tools that I was looking for in order to apply for Data Science jobs. Data Science A-Z course by is very nice & interactive course. I am very impressed with the instructor’s approach in explaining all the data science concepts with related examples.Thanks a million.

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