Data Science with Python Training will help you to become a Master in Python libraries Such as Numpy, Pandas, Matplotlib, Seaborn, Plotly, Scikit-Learn and SciPy for Data Science with Hands-on Projects. This Course provides you the in-depth Knowledge on Statistics, Math and Python Programming to develop Machine Learning algorithms for accurate Predictions with Real-time Projects. Enroll for Data Science with Python Course and Become Certified Data Scientist.

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Data Science with Python Training and Course

Data Science with Python Course Overview

This Comprehensive Data Science with Python training will improve your own Data Analysis, Data Cleansing and Data Visualization Skills with Real life Projects. This Python for Data Science Course gives introduction to Python fundamental Programming for data manipulation, Classification, Cleaning, Reports, Text mining and Functions Concepts to better understanding.

Learn Advanced Statistical analysis, Tableau, SQL, Machine Learning, and Excel from basic to advanced level Techniques with updated 2020 Course Syllabus and Study Materials. This Course will available through Live Instructor Led Classes and also Self-Paced Videos on each topic with unique course Content. Get one-to-one, Fast-Track and Corporate training with Placement assistance like Resume Building and Mock Data Science Interviews.

Enroll for data Science in Python Course and improve your Python Skills you need to become a good data Scientist.

Recommended Data Science with Python Course

Our Data Science with Python Classes will Suitable for Project Managers, Data Analyst, Python Programmers, Tableau & BI Professionals and College graduates with Basic Computer Science and Statistics Skills.

For others we will recommend checking our Beginner Python and Statistic Courses before taking this Python Data Science Course.

Why Data Science with Python Course

Most of the Companies including Google, Twitter, Facebook and Amazon adopt Machine Learning and deep learning technologies for data analysis, data Manipulation, Big data analytics, supervised and unsupervised algorithms and data Visualization. Data Science Certified Professionals are in huge demand and getting high Salary Packages around $200000.

The Data Science with Python training and course enables the learners to gain in-depth knowledge about supervised and unsupervised machine learning algorithms, predictive modeling, and interactive statistical learning, and more with advanced Excel.

The Python training course covers the statistics basics like mean, mode to explore features like Regression, classification, Native Bayes, label encoding, decision trees, data analysis, clustering, cross-validation, random forest, support vector machines, and more. The candidates will be provided with plenty of real-world projects and exercises in the domain of data science and Python, and test how to apply it over the data science, machine learning, and big data. The Data science with Python training covers Python scripts, conditional statements, command-line arguments, expressions, operands, and more.

Upcoming Training Batches

Yuva Sakthi Academy provides flexible timings to all our students. Here is the Python with Data Science Training Course Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.

Time Days Batch Type Duration (Per Session)
8:00AM - 12:00PM Mon - Sat Weekdays Batch 4Hr - 5:30Hrs
12:00PM - 5:00PM Mon - Sat Weekdays Batch 4Hr - 5:30Hrs
5:00PM - 9:00PM Mon - Sat Weekdays Batch 4Hr - 5:30Hrs

Data Science Masters Program Syllabus

Data Science with Python

Module 1: Introduction to Data Science

  • What is Data Science?
  • What is Machine Learning?
  • What is Deep Learning?
  • What is AI?
  • Data Analytics & its types

Module 2: Introduction to Python

  • What is Python?
  • Why Python?
  • Installing Python
  • Python IDEs
  • Installing Python idle for windows,Linux and
  • Creating “Hello World” code

Module 3: Python Basics

  • Introduction to Python
  • Basic Concepts
  • Conditional Statements
  • Control Statements
  • List, Tuples, Dictionary, Set
  • String Functions
  • Mathematical Functions
  • User defined Functions
  • Class and Objects
  • Constructor
  • Inheritance
  • Package
  • Exception handling
  • Lambda Functions
  • File Concepts
  • Date and Regex Function
  • Tkinter Entry
  • Tkinter Checkbox
  • Tkinter Dropdown list
  • Tkinter Radio Button
  • Tkinter Label
  • Tkinter Button
  • Tkinter Menu
  • Tkinter Frame
  • Tkinter MessageBox
  • Tkinter Scroll bar
  • MySql and Sqlite 3 Connection
Hands-on-Exercise-Constructing Operators
  • Practice and Quickly learn Python necessary skills by solving simple questions and problems.
  • how Python uses indentation to structure a program, and how to avoid some common indentation errors.
  • You executed to make simple numerical lists, as well as a few operations you can perform on numerical lists, tuple, dictionary and set

Module 4: Python Packages, Database, Operating System & Tools

  • Pandas
  • Numpy
  • Sci-kit Learn
  • Mat-plot library
  • Seaborn
  • Pillow
  • OpenCV
  • Installing IDLE for windows, Linux and Mac
  • Installing numpy, pandas and matplotlib


  • MySQL
  • MongoDB

Operating System

  • Linux


  • Power BI

Module 5: Importing Data

  • Reading CSV files
  • Saving in Python data
  • Loading Python data objects
  • Writing data to CSV file
  • To generate data sets and create visualizations of that data. You learned to create simple plots with matplotlib, and you saw how to use a scatter plot to explore random
  • You learned to create a histogram with Pygal and how to use a histogram to explore the results of rolling dice of different
  • Generating your own data sets with code is an interesting and powerful way to model and explore a wide variety of real-world
  • As you continue to work through the data visualization projects that follow, keep an eye out for situations you might be able to model with

Module 6: Manipulating Data

  • Selecting rows/observations
  • Rounding Number
  • Selecting columns/fields
  • Merging data
  • Data aggregation
  • Data munging techniques
  • As you gain experience with CSV and JSON files, you’ll be able to process almost any data you want to analyze.
  • Most online data sets can be downloaded in either or both of these From working with these formats, you’ll be able to learn other data formats as well.

Module 7: Statistics Basics

  • Central Tendency
    • Mean
    • Median
    • Mode
    • Skewness
    • Normal Distribution
  • Probability Basics
    • What does it mean by probability?
    • Types of Probability
    • ODDS Ratio?
  • Standard Deviation
    • Data deviation & distribution
    • Variance
  • Bias variance Tradeoff
    • Underfitting
    • Overfitting
  • Distance metrics
    • Euclidean Distance
    • Manhattan Distance
  • Outlier analysis
    • What is an Outlier?
    • Inter Quartile Range
    • Box & whisker plot
    • Upper Whisker
    • Lower Whisker
    • Scatter plot
    • Cook’s Distance
  • Missing Value treatment
    • What is NA?
    • Central Imputation
    • KNN imputation
    • Dummification
  • Correlation
    • Pearson correlation
    • positive & Negative correlation
  • Compute probability in a situation where there are equally-likely outcomes
  • Apply concepts to cards and dice
  • Compute the probability of two independent events both occurring
  • Compute the probability of either of two independent events occurring
  • Do problems that involve conditional probabilities
  • Calculate the probability of two independent events occurring
  • List all permutations and combinations
  • Apply formulas for permutations and combinations

Module 8: Error Metrics

  • Classification
    • Confusion Matrix
    • Precision
    • Recall
    • Specificity
    • F1 Score
  • Regression
    • MSE
    • RMSE
    • MAPE
  • State why the z’ transformation is necessary
  • Compute the standard error of z
  • Compute a confidence interval on ρ The computation of a confidence interval
  • Estimate the population proportion from sample proportions
  • Apply the correction for continuity

Machine Learning

Supervised Learning

  • Linear Regression
    • Linear Equation
    • Slope
    • Intercept
    • R square value
  • Logistic regression
    • ODDS ratio
    • Probability of success
    • Probability of failure Bias Variance Tradeoff
    • ROC curve
    • Bias Variance Tradeoff
  • we’ve reviewed the main ways to approach the problem of modeling data using simple and definite

Unsupervised Learning

  • K-Means
  • K-Means ++
  • Hierarchical Clustering


  • Support Vectors
  • Hyperplanes
  • 2-D Case
  • Linear Hyperplane

SVM Kernal

  • Linear
  • Radial
  • polynomial

Other Machine Learning algorithms

  • K – Nearest Neighbour
  • Naïve Bayes Classifier
  • Decision Tree – CART
  • Decision Tree – C50
  • Random Forest
  • We have covered the simplest but still very practical machine learning models in an eminently practical way to get us started on the complexity
  • where we will cover several regression techniques, it will be time to go and solve a new type of problem that we have not worked on, even if it’s possible to solve the problem with clustering methods (regression), using new mathematical tools for approximating unknown values.
  • In it, we will model past data using mathematical functions, and try to model new output based on those modeling

Artificial Intelligence

Module 1: AI Introduction

  • Perceptron
  • Multi-Layer perceptron
  • Markov Decision Process
  • Logical Agent & First Order Logic
  • AL Applications

Deep Learning

Module 1: Deep Learning Algorithms

  • CNN – Convolutional Neural Network
  • RNN – Recurrent Neural Network
  • ANN – Artificial Neural Network
  • We took a very important step towards solving complex problems together by means of implementing our first neural
  • Now, the following architectures will have familiar elements, and we will be able to extrapolate the knowledge acquired on this chapter, to novel

Introduction to NLP

  • Text Pre-processing
  • Noise Removal
  • Lexicon Normalization
  • Lemmatization
  • Stemming
  • Object Standardization

Text to Features (Feature Engineering)

  • Syntactical Parsing
  • Dependency Grammar
  • Part of Speech Tagging
  • Entity Parsing
  • Named Entity Recognition
  • Topic Modelling
  • N-Grams
  • TF – IDF
  • Frequency / Density Features
  • Word Embedding’s

Tasks of NLP

  • Text Classification
  • Text Matching
  • Levenshtein Distance
  • Phonetic Matching
  • Flexible String Matching
  • provided, you will even be able to create new customized
  • As our models won’t be enough to solve very complex problems, in the following chapter, our scope will expand even more, adding the important dimension of time to the set of elements included in our generalization.

Project Works

Project 1: Board Game Review Prediction

  • To perform a Linear regression
  • Analysis by predicting the average reviews in a board game

Project 2 :Credit Card Fraud Detection

  • TO focus on Anomaly Detection by using probability densities to detect credit card fraud

Project 3: Stock Market Clustering

  • Learn how to use the K-means clustering
  • To find related companies by finding correlations among stock market movements over a given time span

Project 4: Getting Started with Natural Language Processing

  • will focus on Natural Language Processing (NLP) methodology, such as tokenizing words
  • and sentences, part of speech identification and tagging, and phrase

Project 5: Obtaining Near State-of-the-Art Performance on Object Recognition

  • Using Deep Learning – In this project, will use the CIFAR-10 object recognition dataset as a
  • benchmark to implement a recently published deep neural

Project 6: Image Super Resolution with the SRCNN – Learn how to implement & use

  • Tensorflow version of the Super Resolution Convolutional Neural Network (SRCNN) for
  • improving image

Project 7: Natural Language Processing: Text Classification

  • an advanced approach to Natural Language Processing by solving a text classification task
  • using multiple classification

Project 8: K-Means Clustering For Image Analysis

  • use K-Means clustering in an unsupervised learning method to analyze and classify 28 x 28 pixel images from the MNIST

Project 9:Data Compression & Visualization Using Principal Component Analysis

  • This project will show you how to compress our Iris dataset into a 2D feature set and how to visualize it through a normal x-y plot using k-means clustering


Module 1: Tableau Course Material

  • Start Page
  • Show Me
  • Connecting to Excel Files
  • Connecting to Text Files
  • Connect to Microsoft SQL Server
  • Connecting to Microsoft Analysis Services
  • Creating and Removing Hierarchies
  • Bins
  • Joining Tables
  • Data Blending

Module 2: Learn Tableau Basic Reports

  • arameters
  • Grouping Example 1
  • Grouping Example 2
  • Edit Groups
  • Set
  • Combined Sets
  • Creating a First Report
  • Data Labels
  • Create Folders
  • Sorting Data
  • Add Totals, Subtotals and Grand Totals to Report


  • Install Tableau Desktop
  • Connect Tableau to various Datasets: Excel and CSV files

Module 3: Learn Tableau Charts

  • Area Chart
  • Bar Chart
  • Box Plot
  • Bubble Chart
  • Bump Chart
  • Bullet Graph
  • Circle Views
  • Dual Combination Chart
  • Dual Lines Chart
  • Funnel Chart
  • Traditional Funnel Charts
  • Gantt Chart
  • Grouped Bar or Side by Side Bars Chart
  • Heatmap
  • Highlight Table
  • Histogram
  • Cumulative Histogram
  • Line Chart
  • Lollipop Chart
  • Pareto Chart
  • Pie Chart
  • Scatter Plot
  • Stacked Bar Chart
  • Text Label
  • Tree Map
  • Word Cloud
  • Waterfall Chart
  • Create and use Static Sets
  • Create and use Dynamic Sets
  • Combine Sets into more Sets
  • Use Sets as filters
  • Create Sets via Formulas
  • Control Sets with Parameters
  • Control Reference Lines with Parameters

Module 4: Learn Tableau Advanced Reports

  • Dual Axis Reports
  • Blended Axis
  • Individual Axis
  • Add Reference Lines
  • Reference Bands
  • Reference Distributions
  • Basic Maps
  • Symbol Map
  • Use Google Maps
  • Mapbox Maps as a Background Map
  • WMS Server Map as a Background Map
  • Create Barcharts
  • Create Area Charts
  • Create Maps
  • Create Interactive Dashboards
  • Create Storylines
  • Understand Types of Joins and how they work
  • Work with Data Blending in Tableau
  • Create Table Calculations
  • Work with Parameters
  • Create Dual Axis Charts
  • Create Calculated Fields

Module 5: Learn Tableau Calculations & Filters

  • Calculated Fields
  • Basic Approach to Calculate Rank
  • Advanced Approach to Calculate Ra
  • Calculating Running Total
  • Filters Introduction
  • Quick Filters
  • Filters on Dimensions
  • Conditional Filters
  • Top and Bottom Filters
  • Filters on Measures
  • Context Filters
  • Slicing Fliters
  • Data Source Filters
  • Extract Filters
  • Creating Data Extracts in Tableau
  • Understand Aggregation, Granularity, and Level of Detail
  • Adding Filters and Quick Filters

Module 6: Learn Tableau Dashboards

  • Create a Dashboard
  • Format Dashboard Layout
  • Create a Device Preview of a Dashboard
  • Create Filters on Dashboard
  • Dashboard Objects
  • Create a Story

Module 7: Server

  • Tableau .
  • Overview of Tableau
  • Publishing Tableau objects and scheduling/subscription.
  • Create Data Hierarchies
  • Adding Actions to Dashboards (filters & highlighting)
  • Assigning Geographical Roles to Data Elements
  • Advanced Data Preparation

Python Training Trainer Profile

A Python trainer at Yuva Sakthi Academy gives total freedom to their students to explore, examine and learn Python courses based on real-time examples.

  • They are certified and working professionals with outstanding grades.
  • They are currently working as Python professionals with the top MNC city.
  • They are well connected with hiring H.R.s in multinational companies.
  • They have practical communication skills to deliver the course with suitable examples in each Python class.
  • They have strong practical and theoretical knowledge of essential Python and Python Machine learning concepts.
  • They have expert-level subject knowledge.
  • Our trainers are continuously updated on industry trends and expectations to include them in the python programming project and corporate training.
  • Our instructors are entirely committed to helping our trainees advance in their jobs and get internship opportunities.
  • They offer all available assistance to participants to achieve their Python language learning objective and prepare them to face their interviews confidently.

Become a Python Certified Professional

Yuva Sakthi Academy is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.

Our at Yuva Sakthi Academy is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this in leading MNC’s of the world. The is only provided after successful completion of our training and practical based projects.

Yuva Sakthi Academy Python Certificate will help you to boost your career. You Can Complete this within 3 months and is designed for 3 levels Beginner, intermediate and expert Levels which is Suitable for Freshers, seniors, and Project Managers respectively. 3000+ Certified Students on Yuva Sakthi Academy Branches.
This Course will teach you Django and GitHub with Practical examples. By completing this you may get offers from top MNC like Google, Amazon, Flipkart, JPMorgan chase, and Infosys.
We recommended this yuva sakthi academys Academy Python Course for you to get a strong programming foundation and better career opportunity in the Software industry. Students can avail of this Course through Classroom or Online Classes.

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I highly recommend the computer training institute for anyone who wants to improve their computer skills. The instructors are knowledgeable and patient, and they create a comfortable and supportive learning environment. The curriculum is well-structured and covers a range of topics, from basic computer operations to advanced programming languages.



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Frequently Asked Questions

Will I be able to get job assistance after I finish my Python Training ?

Yes, we have a list of more than 2000 students who got placed last year. Yuva Sakthi Academy conducts development sessions that include mock interviews and presentation skills to educate students to handle challenging interviews with comfort. Most importantly, we have dedicated placement portals that cater to students’ needs during placements.

Where can I enroll for the best python course near me ?

Yuva Sakthi Academy has been providing the best Python course training and has more than 20+ branches all over India. Most importantly, we have affordable python costs.

What is the proficiency after Python Training?

With fewer lines of code, you can create more complicated programs. Moreover, Python can help you make more secure web solutions by assisting you with secure programming and resolving issues.

What are the job options after successful completion of the Python Course ?

Following are the job options after Python course completion

  • Python Developer
  • Python Software Engineer
  • Python Application Engineer
  • Android Software Developer
  • Data Analyst
  • Software Programmer
  • Full-Stack Developer
  • Research analysts
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Yuva Sakthi Academy shapes your skills and helps you land your dream job roles.

Why learn a python programming language?

Python is one of the most prominent programming languages in the world. It is simple to learn and flexible to use. The best part is now the python programmers need not be restricted to only data science; they can explore other fields like Basic game development, Web development, Security and penetration testing, Mapping and geography (GIS software), Scientific and mathematical computing, computer graphics, Artificial Intelligence applications with Python, and so on. The course educates you on data operations, conditional statements, strings, error handling, and Django (Python Web framework). To know more, browse our Python Tutorial.

What is a career in Python after Python training ?

Python engineers are in high demand year after year, and it also provides the most promising job chances for individuals, making it the most popular programming language.

  • Python programming language provides concise codes with faster readability that are not available in other programming languages.
  • You can construct dynamic scripts on small and large scales using the Python programming language.
  • Python has a wide range of applications; we may use it for web development, application development, testing, scriptwriting, and program updates, among other things.
  • If you want to seek a career in Python, you will have more options than in any other programming language.
  • If you become a data scientist, you will increase the value of data for your company. If you become a software developer, you will excel in the Python programming language.
  • You will have many options, whether you are a seasoned Python coder or a newcomer to the area.

Will I get a Python Course Completion from Yuva Sakthi Academy?

Yes, after successful course completion, you will be awarded a course completion certificate from Yuva Sakthi Academy.

Whom should I contact if I have queries about the Python and Django Course ?

You can reach out to our course advisor by calling on +91-9597684055, and our course advisor will assist you. You can also send us your queries on our email yuvasakthiacademycbe@gmail.com

What are the different modes of payment available for Python Course fees ?

We accept all modes of payment options: cash, card (Master, Visa, and Maestro), Net Banking, etc.

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Learn Python Training from Python Experts. Build your Career in Python Programming. It’s a Right time to learn Python Course from Basic to Advanced level with Placements. Python Programmers are some of the highest Paid in the industry, with average Salaries over $100000. This Python Training will help you to get a valid lifetime industry-recognized Credential and become a best Python Developer!
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Below are the Python implementations that we see in the coding world.

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Python’s easy and diverse nature made a place in the top most popular programming language of 2018. Making Python a good career choice for an apprentice.

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Learning python as such does not require any deep knowledge of programming. But if you have prior experience of coding and programming than it is a plus point for the learner.

Important Features

Python® can communicate to other parts of the application using the variety of component integration. For an example using CPython component, python can call C/C++ libraries and can be called from C/C++ programs. It will also have support for accessing java objects, .NET objects through Jython, IronPython respectively.
As in Python, everything is the object, every operation seems to be easier than other scripting languages. Python® codes are equal to one third and one-fifth of C/C++ and Java programs in term of a number of lines. It has powerful memory management to reuse garbage collections.
Python supports different types of objects like numbers, string, tuples, list, the dictionary to store data and do operations on stored data. It has common methods and operations on sequence objects ( list, string, tuples ) like indexing, slicing, extended slicing.

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Apart from Ruby, after Swift, Python developers are more in demand and thus earns large packages. Python is also in use for cyber security. The super-intelligent coding structure provides different ways for supporting modern high-end technologies.

Advanced Python Training

Python Introduction

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This Best Python Courses will help you to understand on Creating Web development using Django Framework with Responsive and Efficient Manner. Python offers wide dimensions when it comes to web development. It offers numerous structures from which to browse including bottle.py, Jar, CherryPy, Pyramid, Django, and web2py. These structures have been utilized to control a portion of the world’s most mainstream websites, for example, Spotify, Mozilla, Reddit, the Washington Post, and Yelp. You can learn strategies used in the improvement of Python Web applications and spotlight on the best way to program true answers for issues that customary individuals really need to fathom.

What you will learn:

Python for Programmers:

If you wish to learn a Programming Language in the current Scenario to start your career in IT Field then Choose Python Programming for a better future. We Offer the Python Training for College Students, Working Professionals, and Non-IT Professionals at very low fees from 2010. Before the finish of the course, you will have a decent comprehension of the main Python dialect, Python’s incredible implicit information types, and the essentials of article situated programming in Python. You can gain experience utilizing expressive Python colloquialisms, see how modules and packs work, Python’s coding style rules, and how to compose unit tests for Python code. You will likewise think about how to peruse, compose, picture, and perform an amazing spellbinding examination on datasets (counting CSV, Exceed expectations, and SQL) and how to utilize Python to devour the web APIs and to make your very own web APIs. You will likewise comprehend the polish and intensity of the dialect and you will be very much put to keep adapting more as you use it every day.

Python Developer Sample Resume

Sample Resume 1

Nearly 3 years of total IT experience and currently working as a python developer at Company Name, I have created and implemented a Python-based web application on Django. Deep expertise in Django Framework.
Extensive Experience in working with Python frameworks such as NumPy, Pandas, Django, and SciKit Learn.
Work Experience:
Current Location:
Total Work Experience:
Project Name:
Project Highlights:

  • E-Commerce System and Recommender System:
  • E-Commerce System based on the Security API and Authentication API.
  • This system is used to post the Product and order the Product, Tracking the Order, cancellation, Authentication and Recommender System
  • Real Estate Application
  • Grant Permission for Realtors to Post the Details
  • Users can access the details and chat with realtors
  • Implemented chatbot
  • Dashboard for Realtors and Users

Key Responsibilities Handled:

  • Extensively worked on API handling on-Django.
  • Extensively worked on database schema conversion tool for converting source database schema which will be compatible with the target database.
  • Successfully migrate databases such as oracle, server, dynamo DB to Django Application.
  • Worked on a different scenario such as a retrieving from API, Posting to Database, writing database models in Python.
  • Good experience of Pandas and Retrieving from Pandas
  • Web-based development experience utilizing Python
  • Understand security best practices, policies and standards to design highly secure on Payment Integration, Authentication
  • Support the setup, configuration, and maintenance of an SQL Server
  • Architect’s and Implemented AWS Cloud cost-effective solution for Non-Production environments such as Development, Testing, etc.
  • Solid experience in Perl and Python, with OO Experience (key)
  • A strong understanding of common web development techniques, e.g. REST, JSON, etc
  • Appreciation of the development of a secure scalable system
  • Development experience of event-driven asynchronous systems

Competencies Include:

  • Experience of working and delivering in extreme stressed and demanding conditions
  • Knowledge of basic Linux commands.

Technical Expertise:

  • Python Scripting
  • SQL Servers
  • Frameworks like Django, Tkinter, and Pandas

Tools & Other Software:

  • Database – MySQL

Educational Qualifications:
Degree/Certificate Year Institute/School, City %/CGPA
B.E. in Electronics &Telecommunication 2011-2015 Satyabhama University, coimbatore. 7.2
s and Training Completed
Python Basic Foundation – From Yuva Sakthi Academy
Achievements & Co-Curricular Activities:

  • Received Spot Recognition Award several times for the stretch and dedication I possessed.
  • Quality spoc for the team and handled several PQI and SSAE audit.
  • Part of Syntel cricket and won various corporate level tournaments.

I hereby declare that the information furnished above is true and correct to the best of my knowledge and belief.

Sample Resume 2

I am a Project Engineer with 5 years and 9 months of experience in Wintel & Active Directory administration. I pursued B.E – Electronics and Instrumentation Engineering. Currently pursuing MBA-Finance, Anna University. Also, I am equipped with DELF- A1 – French language . I am looking forward to utilizing skills in a challenging environment to enhance my career and personal growth.
Work Experience:
Developer:  Company Name
Years of experience:
Key Responsibilities Included:

  • Developing and Managing the Application
  • Implementing, configuring, and troubleshooting of Virtual Machines.
  • Responsible for programming, developing and documenting interactive Web applications and automation procedures
  • Creating, maintaining and updating various Web applications created primarily in Python
  • Strong Python systems programming experience
  • Strong OO design and programming experience
  • Experience with Git, Node.js, Python, Java, HTML5, CSS3, Shockwave Flash, or Apache Tomcat
  • Experience with NoSQL, and MongoDB
  • Experience with Open Source visual analytics platforms, including Lyra, Map Story, or Flex maps
  • Experience with trust models for data or expert opinions
  • Experience with deploying applications in a Cloud environment
  • Experience with designing and developing automated analytic software, techniques, and algorithms

Python Senior Developer
Company Name:
Work During: 2014 – 2016
Key Responsibilities as Python Developers included

  • Analyzing and Processing the Data
  • Administration of Dev and test environment.
  • Daily sales report monitoring.
  • SaaS design / RESTful API integration
  • Building applications in scripting languages in PYTHON
  • Understanding relational databases/data models

Key responsibilities as Python Automation Developer included:

  • Working knowledge of Memcache, Redis, and Varnish
  • Experience with Grunt, Bower, and similar package management tools
  • Experience with frontend unit testing via Mocha, Chai, or Jasmine and Karma
  • Expertise in Git
  • Experience working within AWS, specifically EC2, RDS, SQS, SNS, S3, and ElasticCache
  • Working knowledge of operations, command-line tools, diagnostics and debuggers
  • Experience leading development teams using Agile methodologies
  • Familiarity with vagrant, docker, and/or dies
  • Familiarity with continuous integration. Specifically, Travis CI and/or Jenkins
  • Familiarity with different design patterns
  • Experience building and consuming RESTful services
  • A service-oriented approach to application development
  • Knowledge of unit, functional, and load testing software and best practices
  • Adaptability and the ability to evaluate the right tools for the job
  • A desire to learn and a desire to share knowledge
  • A meticulous and passionate approach to performance optimization and debugging
  • Marionette experience
  • Gitflow experience
  • Experience with Ad and Reporting library integration

Python Developer
Company Name:
Work During: 2013 – 2014
Key responsibilities included:

  • 5+ years of Python scripting experience
  • Business process engineering experience
  • Experience with an object-oriented database
  • Experience doing test-driven development, functional testing and continuous integration

DELF – A1 – French Language.
Alliance Française of Madras – 2016
B.E- Electronics and Instrumentation – Sri Sai Ram Engineering College (2008 – 2012)
GPA: 7.5
MBA (Finance) –  Anna University (Pursuing) Nov 2014- Present
Intensive English Language Course – British Council (Pursuing) Nov-2018
Planning to appear for IELTS by January 2019
Skills & Recognition
Knowledge in AD infrastructure (Directory Replication, group policy, security, schema changes, etc.)

  • Created basics scripts for health checks
  • System Improvement Plan (SIP)
  • Systematic Operating Procedure (SOP)
  • French A1 Certified
  • Team Lead
  • Lean (Basic)
  • Best Performer award for incident reduction and multiple team handling
  • Received client appreciation for implementing emergency changes on -time
  • Received Outstanding and Excellent contribution rating in previous appraisals

1. Tushar Punekar
Company: Wipro Technologies, UK
Designation: Senior Project Manager
Telephone: +44-7448200963
2. Mohammed Asif
Company: Wipro Technologies, UK
Designation: Project Manager
Telephone: +44-7723483823

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