Data Science With Python – Best Data Science With Python  Training Institute in Chennai

About Data science:

  How to extract insights from Data which includes structured and unstructured data.
  Unifies statistics, data analysis and their related methods to analyze data.
  Uses techniques and ideas from various fields such as mathematics, statistics, and computer science (Databases, machine learning etc).
  Used commonly in business analytics only because other alternatives like Big Data and Machine learning had grown enormously in recent years.

About Python:

  Popular high-level general-purpose programming language.
  Created by Guido van Rossum and released in 1991.
  Open source and community based development.
  Its two important features are code readability and the syntax.
  Code readability means the use of white space in the place of braces.
  Its syntax needs fewer lines of code than all other programming languages.
  Used in various domains such as web applications, internet scripting, database and gaming.

Course

Syllabus
  Crafted to provide the bests of Data science and Python to our students.
  Tailored to fulfill the expectations of the IT industry.
  Comprehensive enough to master both Data science and Python.
  Prepared by a team of experts who also prepared the study materials.
  Includes many case studies and real-life examples.

Trainers
  Professionals with maximum expertise and 10+ years of work experience.
  Have immense knowledge in both Data science and Python.
  Kind and helping teachers who prioritizes the education of students over comfort.
  Clears the doubts of students after every class or at the earliest possibility available.
  Provides counselling and feedbacks to our students whenever needed.

Infrastructure
  Up-to-date computer lab with Python and other Data science tools required.
  Projector-friendly smart classrooms and spacious and calm study halls.
  Video-conferencing enabled classrooms to conduct webinars and guest lectures.
  Free High-speed Internet to encourage our students learn more.

Placements
  100% placement record in all the years till now.
  Our placement cell work hard to ensure that all of our students are placed.
  Help to prepare a remarkable Resume.
  Provide a lot of study materials for interview preparation.
  Conduct a lot of mock tests and interviews to boost the confidence of our students.

There are also other benefits in choosing the Best training institute to learn Data science with Python such as

  Various batch timings to admit students, to-be employed and employed professionals.
  Flexible fees structure and payment methods to help the needy students.
  Access to an online library containing information about Data science and Python.
  1-to-1 training and online training can be arranged if informed earlier.

Placements
  100% placement record in all the years till now.
  Our placement cell work hard to ensure that all of our students are placed.
  Help to prepare a remarkable Resume.
  Provide a lot of study materials for interview preparation.
  Conduct a lot of mock tests and interviews to boost the confidence of our students.

There are also other benefits in choosing the Best training institute to learn Data science with Python such as

  Various batch timings to admit students, to-be employed and employed professionals.
  Flexible fees structure and payment methods to help the needy students.
  Access to an online library containing information about Data science and Python.
  1-to-1 training and online training can be arranged if informed earlier.

Various batch timings to admit students, to-be employed and employed professionals.
  Flexible fees structure and payment methods to help the needy students.
  Access to an online library containing information about Data science and Python.
  1-to-1 training and online training can be arranged if informed earlier.er.

DataScience with Python Course Syllabus

Lesson 1: Data Science Overview
  Data Science
  Data Scientists
  Examples of Data Science
  Python for Data Science

Lesson 2: Data Analytics Overview
  Introduction to Data Visualization
  Processes in Data Science
  Data Wrangling, Data Exploration, and Model Selection
  Exploratory Data Analysis or EDA
  Data Visualization
  Plotting
  Hypothesis Building and Testing

Lesson 3: Statistical Analysis and Business Applications
  Introduction to Statistics
  Statistical and Non-Statistical Analysis
  Some Common Terms Used in Statistics
  Data Distribution: Central Tendency, Percentiles, Dispersion
  Histogram
  Bell Curve
  Hypothesis Testing
  Chi-Square Test
  Correlation Matrix
  Inferential Statistics

Lesson 4: Python: Environment Setup and Essentials
  Introduction to Anaconda
  Installation of Anaconda Python Distribution – For Windows, Mac OS, and Linux
  Jupyter Notebook Installation
  Jupyter Notebook Introduction
  Variable Assignment
  Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
  Creating, accessing, and slicing tuples
  Creating, accessing, and slicing lists
  Creating, viewing, accessing, and modifying dicts
  Creating and using operations on sets
  Basic Operators: ‘in’, ‘+’, ‘*’
  Functions
  Control Flow

Lesson 5: Mathematical Computing with Python (NumPy)
  NumPy Overview
  Properties, Purpose, and Types of ndarray
  Class and Attributes of ndarray Object
  Basic Operations: Concept and Examples
  Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
  Copy and Views
  Universal Functions (ufunc)
  Shape Manipulation
  Broadcasting
  Linear Algebra
  Lesson 6: Scientific computing with Python (Scipy)
  SciPy and its Characteristics
  SciPy sub-packages
  SciPy sub-packages –Integration
  SciPy sub-packages – Optimize
  Linear Algebra
  SciPy sub-packages – Statistics
  SciPy sub-packages – Weave
  SciPy sub-packages – I O

Lesson 7: Data Manipulation with Python (Pandas)
  Introduction to Pandas
  Data Structures
  Series
  DataFrame
  Missing Values
  Data Operations
  Data Standardization
  Pandas File Read and Write Support
  SQL Operation
  Lesson 8: Machine Learning with Python (Scikit–Learn)
  Introduction to Machine Learning
  Machine Learning Approach
  How Supervised and Unsupervised Learning Models Work
  Scikit-Learn
  Supervised Learning Models – Linear Regression
  Supervised Learning Models: Logistic Regression
  K Nearest Neighbors (K-NN) Model
  Unsupervised Learning Models: Clustering
  Unsupervised Learning Models: Dimensionality Reduction
  Pipeline
  Model Persistence
  Model Evaluation – Metric Functions

Lesson 9: Natural Language Processing with Scikit-Learn
  NLP Overview
  NLP Approach for Text Data
  NLP Environment Setup
  NLP Sentence analysis
  NLP Applications
  Major NLP Libraries
  Scikit-Learn Approach
  Scikit – Learn Approach Built – in Modules
  Scikit – Learn Approach Feature Extraction
  Bag of Words
  Extraction Considerations
  Scikit – Learn Approach Model Training
  Scikit – Learn Grid Search and Multiple Parameters
  Pipeline

Lesson 10: Data Visualization in Python using Matplotli
  Introduction to Data Visualization
  Python Libraries
  Plots
  Matplotlib Features:
  Line Properties Plot with (x, y)
  Controlling Line Patterns and Colors
  Set Axis, Labels, and Legend Properties
  Alpha and Annotation
  Multiple Plots
  Subplots
  Types of Plots and Seaborn

Lesson 11: Data Science with Python Web Scraping
  Web Scraping
  Common Data/Page Formats on The Web
  The Parser
  Importance of Objects
  Understanding the Tree
  Searching the Tree
  Navigating options
  Modifying the Tree
  Parsing Only Part of the Document
  Printing and Formatting
  Encoding

Lesson 12: Python integration with Hadoop, MapReduce and Spark
  Need for Integrating Python with Hadoop
  Big Data Hadoop Architecture
  MapReduce
  ClouderaQuickStart VM Set Up
  Apache Spark
  Resilient Distributed Systems (RDD)
  PySpark
  Spark Tools
  PySpark Integration with Jupyter Notebook

There is no Official certification for Data Science with Python but you have separate certifications for Data science. For Python till now there are no official certifications but the process to introduce official certifications has started. We will guide you throughout the process to get the specific Data science certification you prefer and for Python, our course completion certificate along with your own Python program which you did in the practical sessions is more than enough. However, these certifications are not mandatory to get a job because you will be placed in a company of your liking as soon as you had completed our course on Data science with Python

After the completion of our training on Data science with R, you will have numerous job opportunities from all over the world. Some of the positions you will be appointed to, are listed below:

  Data Scientist – Python
  Business Analyst – Python
  Data analyst – Python
  Python Developer – Artificial Intelligence/Machine Learning

Apart from these, there are other additional benefits such as promotions, switching job to a MNC and teaching Data science or Python at institutes or online platforms based on your availability

 Best IT training institute in Chennai with Placement

“You don’t have to believe our words that name Upshot technologies as the Best IT training institute in Chennai but you have to believe the words of our students which are spoken from the experience they had from our training.  ”

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