Course Id: 1016

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn’t catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python’s introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.

Python Programming Course Syllabus

  • Chapter 1: An Introduction to Python
    1. Introductory Remarks about Python
    2. Strengths and Weaknesses
    3. A Brief History of Python
    4. Python Versions
    5. Installing Python
    6. Environment Variables
    7. Executing Python from the Command Line
    8. IDLE
    9. Editing Python Files
    10. Getting Help
    11. Dynamic Types
    12. Python Reserved Words
    13. Naming Conventions
  • Chapter 2: Basic Python Syntax
    1. Introduction
    2. Basic Syntax
    4. String Values
    5. String Operations
    6. The format Method
    7. String Slices
    8. String Operators
    9. Numeric Data Types
    10. Conversions
    11. Simple Input and Output
    12. The print Function
  • Chapter 3: Language Components
    1. Introduction
    2. Control Flow and Syntax
    3. Indenting
    4. The if Statement
    5. Relational Operators
    6. Logical Operators
    7. True or False
    8. Bit Wise Operators
    9. The while Loop
    10. break and continue
    11. The for Loop
  • Chapter 4: Collections
    1. Introduction
    2. Lists
    3. Tuples
    4. Sets
    5. Dictionaries
    6. Sorting Dictionaries
    7. Copying Collections
    8. Summary
  • Chapter 5: Functions
    1. Introduction
    2. Defining Your Own Functions
    3. Parameters
    4. Function Documentation
    5. Keyword and Optional Parameters
    6. Passing Collections to a Function
    7. Variable Number of Arguments
    8. Scope
    9. Functions – “First Class Citizens”
    10. Passing Functions to a Function
    11. Mapping Functions in a Dictionary
    12. Lambda
    13. Closures
  • Chapter 6: Modules
    1. Modules
    2. Standard Modules – sys
    3. Standard Modules – math
    4. Standard Modules – time
    5. The dir Function
  • Chapter 7: Exceptions
    1. Errors
    2. Run Time Errors
    3. The Exception Model
    4. Exception Hierarchy
    5. Handling Multiple Exceptions
    6. raise
    7. assert
    8. Writing Your Own Exception Classes
  • Chapter 8: Input and Output
    1. Introduction
    2. Data Streams
    3. Creating Your Own Data Streams
    4. Access Modes
    5. Writing Data to a File
    6. Reading Data From a File
    7. Additional File Methods
    8. Using Pipes as Data Streams
    9. Handling IO Exceptions
    10. Working with Directories
    11. Metadata
    12. The pickle Module
  • Chapter 9: Classes in Python
    1. Classes in Python
    2. Principles of Object Orientation
    3. Creating Classes
    4. Instance Methods
    5. File Organization
    6. Special Methods
    7. Class Variables
    8. Inheritance
    9. Polymorphism
    10. Type Identification
    11. Custom Exception Classes
    12. Class Documentation – pydoc
  • Chapter 10: Regular Expressions
    1. Introduction
    2. Simple Character Matches
    3. Special Characters
    4. Character Classes
    5. Quantifiers
    6. The Dot Character
    7. Greedy Matches
    8. Grouping
    9. Matching at Beginning or End
    10. Match Objects
    11. Substituting
    12. Splitting a String
    13. Compiling Regular Expressions

  • Regular classes – 4 weeks
  • Weekend Classes – 6 weeks
  • Customized Fast Track option is available as well. Call +91-8049202039 now to customize according to your requirement

  • Experienced IT professionals
  • Having hands on practical knowledge
  • With experience of training large batches in both offline and online mode

The following services are available on demand as add-on to this course

  • Resume Preparation
  • Mock interviews
  • Job opportunity leads and suggestions

  • Online Self Paced Training (SPT) with Videos and Documents
  • Online Instructor Led Training (ILT)

About the course:

Study9 provides a robust job market focused Python  training. Our Python  course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our Python  trainers are experienced professionals with hands on knowledge of Python  projects. The Python  course content is designed with keeping the current job market’s demands in mind.Our Python  training course is value for money and tailor made for our students.

About Study9 Training Method

The Study9 Python  training courses are completely online training courses. The online Python  training is given using advanced training softwares to make the students comfortable with the online training. The student and teacher can talk over VOIP software, they can share each others screens, share Python  course contents and concerns during the class through chat window and even can see each other using Webcams. The time tested proven online Python  training methodologies adopted by study9 are of the most advanced ones in India. The student will feel at ease with the Python  training mode. And we are so confident on that, we offer a moneyback if the student is not satisfied with first Python  Training class.

The  based Python  training course contents are accessible from anywhere in the world. Study9 provides access for each student to an online Learning Management System that holds all the slides and videos that are part of the Python  training courses. The students can access them from their Laptop, Mobile, Tablets etc. The students will also give Python  training exams on this Learning Management System and our expert Python  trainers will rate their papers and provide certifications on successful completion of these Python  training exams.

The best part of this online Python  training approach is that it does not require one to waste time by travelling to a particular Python  training center. And the timings are flexible so that if someday the student has problems in taking the morning Python  training class he/she can fix an alternate time in the evening in discussion with Python  trainer. On need basis our Python  trainers can take a class in late night as well. On request basis missed Python  training class sessions can even be given as video lectures to the student for them to go through to be prepared for the next class.

Schedule: Weekdays (1 hr /day), Weekends (2.5 hrs /day)  and Fast Track options available