Best Python Training in Hyderabad
Python is a versatile language that you can use on the backend, frontend, or full stack of a web application. It’s also one of the easiest languages to learn, which makes it a great choice for beginners. If you’re looking for the best Python training in Hyderabad, Stansys is the perfect place for you. At Stansys, we offer comprehensive Python training that covers everything from the basics to advanced concepts. Our experienced instructors will guide you through each topic and help you build practical skills that you can use in your career. In our Python training program, you’ll learn about data structures, object-oriented programming, file handling, databases, and more. By the end of the course, you’ll be able to confidently build web applications using Python. So if you’re ready to start your journey with Python, sign up for our Python training course today!
Python is an unambiguous, easy-to-read, general-purpose high-level programming language that considers paradigms of structured, procedural, and object-oriented programming.
Python Course Modules
Python Course Modules:
1. Introduction to Python
2. Data Types and Operators
3. Control Flow Statements
4. Functions and Modules
5. Objects and Classes
6. Exceptions Handling
7. Database Connectivity & Accessing Files
8. Regular Expressions & XML Processing
9. Networking Programming
10. GUI Programming
What are the Python Course Pre-requisites?
Python is a versatile language and can be used for a wide variety of applications. However, before diving into Python, it is important to have a strong foundation in programming. This course is designed for students with little or no programming experience.
The course begins with the basics of Python programming, covering topics such as data types, variables, control structures, and functions. Students will then learn how to work with libraries and modules to add functionality to their programs. The course culminates with a project that allows students to put their knowledge into practice.
Career Opportunities After Taking Python Course
Python is not only one of the most popular programming languages but also one of the easiest to learn. That’s one of the reasons why the interpreted, high-level, general-purpose programming language has been gaining popularity lately.
If you are looking for a career change or want to start your career in programming, learning Python is a great choice. After completing a Python course from a reputed institute like Stansys Software solutions, you will be able to apply for various roles such as Python Developer, Software Engineer, Research Analyst, and Data Scientist.
As a Python developer, you will be responsible for writing and testing code, debugging programs, and integrating applications with third-party web services. As a software engineer, you will be involved in the development and maintenance of software applications. And as a research analyst or data scientist, you will use Python to analyze data and generate insights that can help organizations make better decisions.
So if you are looking for an exciting and rewarding career in programming, learning Python is the right choice for you!
Python Training with Real-Time projects
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. It provides constructs that enable clear programming on both small and large scales. Python is a popular language for web development, scientific computing, data analysis, artificial intelligence, and scripting.
Stansys Software solutions offer the best Python training in Hyderabad with real-time projects to help students gain practical experience. Our experienced faculty will guide you through the concepts of Python and its various libraries. You will also get to work on live projects under the guidance of our experts. This will give you hands-on experience working with Python and help you understand its applications in the real world.
Python Online Training in Hyderabad
Best Python Training Institutes in Hyderabad
Stansys Software Solutions is the best Python training institute in Hyderabad that offers practical exposure to high-end techniques in Python programming. The course curriculum is designed by industry experts keeping in view the current trends and requirements of the IT industry.
The institute provides excellent infrastructure and facilities for students. The world-class faculty at Stansys equips students with the in-depth knowledge and skills required to become successful Python programmers.
Some of the key features of the institute are:
* Experienced and certified instructors
* Industry standard curriculum
* Affordable fees
* Flexible batch timings
* Placement assistance
Why Choose Us for Python Training?
Finding the best Python training institute in Hyderabad is not an easy task with numerous institutes claiming to provide the best training. Stansys Software Solutions is one of the leading python training institutes in Hyderabad that offers comprehensive training on the Python programming language. The course curriculum is designed by experienced industry professionals to meet the latest industry trends and requirements. The training covers all the basics of Python programming language such as data types, variables, loops, Functions, etc. Stansys also provides placement assistance to its students. The institute has a team of experienced placement coordinators who help students prepare for interviews and guide them to get placed in reputed companies. If you are looking for a comprehensive python course in Hyderabad then Stansys is the right place for you.
Python
- Getting started with Python
- Python Overview
- About Interpreter languages
- Advance /Disadvantages of Python
- Starting Python
- Interpreter Path
- Using the interpreter
- Running a Python Script
- Using variable
- Keywords
- Built-In Function
- String Different Literals
- Math Operators and Expressions
- Writing on the screen
- String formatting
- Command line parameters and Flow control
Sequence and File operations
- string
- Lists
- Tuples
- Set
- Dictionary
- Indexing and Slicing
- Iterating through a sequence
- Functions for all sequence
- Using Enumerate()
- Operators and Keywords for sequence
- The xrange() Function
- List comprehensions
- Generator expression
 Deep Dive – Function sorting Error and Exception Handling
- Functions
- Functions parameters
- Variable scope and Returning values. sorting
- Alternative Keys
- Lambda Functions
- Sorting collection of collections
- Sorting dictionaries
- Sorting list in place
- Errors and Exceptions handling
- Handling Multiple Exceptions
- The standard Exception hierarchy
- Using Modules
- The import statement Module search path
- Package installation ways
Regular Expressionist’s Packages and Object oriented programming in python
- The Sys Module
- Interpreter iteration
- STDIO
- Launching external programs
- Paths Directories and filenames
- Walking Directory tree
- Math function
- Random numbers
- Zipped Archives
- Introduction to Python class
- Defining classes
- Initializes
- Instance Methods
- Properties
- Class Methods and Data Static Methods
- Private Methods and Inheritance
- Module Aliases and Regular Expressing
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 Debugging, Databases and project skeletons
- Debugging
- Dealing with Errors
 Machine Learning Using Python
- Machine Learning
- What Is Machine Learning?
- Categories of Machine Learning
- Supervised Machine Learning
- Unsupervised Machine Learning
- Examples of products using machine learning
Clustering
- Similarity Metrics
- Distance Measure Types: Euclidean, Cosine Measures
- Creating predictive models
- Understanding K-Means Clustering
- Understanding TF-IDF, Cosine Similarity and their application
- to Vector Space Model
- Case study
Implementing Associations rule mining
- Similarity Metrics
- What is association rules & Its Use cases ?
- What is Recommendation Engine & It’s working
- Recommendation use-case
- Case study
Decision Tree Classifier
- How to build Decision Tree
- What is classification an its cases ?
- What is Decision tree
- Algorithm for Decision tree induction
- Creating a Decision Tree
- Confusion matrix
Case study
Random Forest Classifier
- What is random forest
- Feature or random Forest
- Out of Box Error Estimate and Variable
- Importance
- Case study
Naive Bayes Classification
- Bayesian Classification
- Gaussian Naive Bayes
- Multinomial Naive Bayes
- When to Use Naive Bayes
- Application : Identify category from text
Linear Regression
- Using House Price Prediction
- Simple Linear Regression
- Polynomial Linear Regression
- Cost Function of Linear Regression
- Understanding linear regression using matrix
 Logistic Regression
- Using Iris dataset to understand logistic regression
- Concept of linearly separable data
- Cost Function & Mathematical Foundation
 k-Means Clustering
- Nearest Neighbours
- Understanding cost function for unsupervised algorithms
- Elbow rule to decide number of clusters
- Application : Image compression
- Application : Detection of number of characters in Arabic
Text Mining
- Case StudyÂ
Sentimental Analysis
- Case study
Support Vector Machines
- Case study
- Introduction to SVM
- SVM History
- Vector Overview
- Decision Surfaces
- Liner SVMs
- The Kernal Trick
- Non-Liner SVM’s
- The Kernal SVM
Deep Learning
- Case study
- Deep learning overview
- The brain vs Neuron
- Introduction to Deep Learning
 Keras
- Introduction to keras – a convient way to code Neural Network
- What is a convolution neural network
- How does a CNN work
CNN & RNN’s
- Creating a convolution neural network from scratch
- What are RNN’s – Introduction to RNN’s
- Recurrent Nerual Network RNN in Python
- LSTM’s for beginners – undersanding LSTM’s
- Long short term memory neural network LSTM in Python
Convolution Neural Network :
- Convolutional Operation
- Relu Layers’
- What is pooling vs Flattening
- Full connection
- Softmax vs Cross Entropy
What are RNN’s Introduction to RNN’s
- Recurrent Neural Network RNN
- LSTM’s for Beginners – understanding LSTM’s
- Long short term memory neural network LSTM in Python
 Time series Analysis
- Describe Time series data
- Format your time series data
- List the different components of Time series data
- Discuss different kind of Time Series scenarios
- Choose the model according to the time series scenario
- Implement the model for forecasting
- Explain working and implementation of ARMA Model
- Illustrate the working and implementation of different ETS Models
- Forecast the data using the respective model
- What is Time series data?
- Time series variable
- Different components of Time Series data
- Visualize the data to identify time series component
- Implement ARIMA Model for forecasting
- Exponent smoothing model
- Identifying different time series scenario based on which different exponential smoothing model can be applied
- Implement respective model for forecasting
- Visualizing and formatting time series data
- Plotting decomposed time series data plot
- Applying ARIMA and ETS Model for time Series forecasting
- Forecasting for given Time Period
- Case study
 Introduction to Artificial Neural Network
- The Details ANN
- The Activation Functions
- How do ANN work & Learn
- Gradient Descent
- Stochastic Gradient Descent
- Back propagation
  Introduction to Hadoop
Introduction to SPARK
FACULTY NAME: LAKSHMI NARAYANA
EXPERIANCE: Python programmer
