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Data Science With Python

  • 40 Hours

Igmguru’s Python online training make you master the ideas and gain in-depth expertise on writing python code and packages like SciPy, Matplotlib, Pandas, Scikit-Learn, NumPy, internet scraping libraries, Lambda function moreover you'll find how to write Python code for large knowledge systems like Hadoop & spark.

Key Features

  • Instructor Led Training : 40 Hrs
  • 100% money back guarantee
  • Flexible Schedule
  • 24 X 7 Lifetime Support & Access
  • Experienced Trainers
  • 100% Job Assistance
  • Get Certified & Get Placed

For Individuals

Online Class Room Program

Online Class Room Program

  • 90 days of access to 1+ instructor-led online training classes
  • 180 days of access to high-quality,self-paced learning content designed by experts
  • $230.57

100% Money Back Guarantee ?

Batches start from 15 Dec 2018.

Overview

IgmGuru's Python online training course is a full course which will make you to obviously perceive the high -level, general dynamic programing language. During Python programming training, you may be exposed to the essential and advanced ideas of Python like machine learning, Hadoop streaming, Deep Learning, MapReduce in Python, and work with packages like Scikit and Scipy. There are many great advantages to learn python online.

What skills will you grasp in Python Online Training Course?

  • Aware of the fundamentals, significance, and installation of Python
  • Aware of file and sequence operations
  • AWare of MapReduce ideas for Hadoop readying
  • Learn OOP, expressions, data types, looping, etc.
  • You will grasp the knowledge of SQLite in Python, functions, operations and sophistication process
  • Use Python language for writing and deploying Pig UDF and Hive UDF
  • Get to know about the Machine Learning Algorithms in Python
  • You will work on a real-life Hadoop project running on Python

Who should go for this training course?

Following IT individuals can join the Python Online Training Course:

  • BI Managers and Project Managers
  • Software Developers and ETL professionals
  • Analytics professionals
  • Big Data professionals
  • Those wanting to have a career in Python

What are the prerequisites for learning Python?

You don’t need to have any specific knowledge to learn Python. A basic knowledge of programming can help

Why Should I need to learn Python Programming Language?

Python is a very fashionable object-oriented language that's quick to be told and straightforward to deploy. It will run on various systems like Windows, UNIX system, and mac so build it extremely needful for the info analytics domain. Upon completion of Python certification training, you'll able to add the large knowledge Hadoop surroundings for terribly high salaries.

  • Python’s design & libraries will provide 10x productivity compared to C, C++, or Java
  • An experienced Python Developer in the United States can earn $102,000 – indeed.com

Modules

Lesson 1 - Data Science Overview

  • 1.1 Data Science
  • 1.2 Data Scientists
  • 1.3 Examples of Data Science
  • 1.4 Python for Data Science

Lesson 2 - Data Analytics Overview

  • 2.1 Introduction to Data Visualization
  • 2.2 Processes in Data Science
  • 2.3 Data Wrangling, Data Exploration, and Model Selection
  • 2.4 Exploratory Data Analysis or EDA
  • 2.5 Data Visualization
  • 2.6 Plotting
  • 2.7 Hypothesis Building and Testing

Lesson 3 - Statistical Analysis and Business Applications

  • 3.1 Introduction to Statistics
  • 3.2 Statistical and Non-Statistical Analysis
  • 3.3 Some Common Terms Used in Statistics
  • 3.4 Data Distribution: Central Tendency, Percentiles, Dispersion
  • 3.5 Histogram  Bell Curve  Hypothesis Testing
  • 3.6 Chi-Square Test  Correlation Matrix  Inferential Statistics

Lesson 4 - Python: Environment Setup and Essentials

  • 4.1 Introduction to Anaconda
  • 4.2 Installation of Anaconda Python Distribution - For Windows, Mac OS, and Linux
  • 4.3 Jupyter Notebook Installation  Jupyter Notebook Introduction
  • 4.4 Variable Assignment
  • 4.5 Basic Data Types: Integer, Float, String, None, and Boolean; Typecasting
  • 4.6 Creating, accessing, and slicing tuples
  • 4.7 Creating, accessing, and slicing lists
  • 4.8 Creating, viewing, accessing, and modifying dicts
  • 4.9 Creating and using operations on sets
  • 4.10 Basic Operators: 'in', '+', '*'  Functions  Control Flow

Lesson 5 - Mathematical Computing with Python (NumPy)

  • 5.1 NumPy Overview
  • 5.2 Properties, Purpose, and Types of ndarray
  • 5.3 Class and Attributes of ndarray Object
  • 5.4 Basic Operations: Concept and Examples
  • 5.5 Accessing Array Elements: Indexing, Slicing, Iteration, Indexing with Boolean Arrays
  • 5.6 Copy and Views  Universal Functions (ufunc)
  • 5.7 Shape Manipulation  Broadcasting  Linear Algebra

Lesson 6 - Scientific computing with Python (Scipy)

  • 6.1 SciPy and its Characteristics  SciPy sub-packages
  • 6.2 SciPy sub-packages –Integration  SciPy sub-packages – Optimize
  • 6.3 Linear Algebra
  • 6.4 SciPy sub-packages – Statistics  SciPy sub-packages – Weave
  • 6.5 SciPy sub-packages - I O

Lesson 7 - Data Manipulation with Python (Pandas)

  • 7.1 Introduction to Pandas
  • 7.2 Data Structures  Series  DataFrame  Missing Values
  • 7.3 Data Operations  Data Standardization
  • 7.4 Pandas File Read and Write Support
  • 7.5 SQL Operation

Lesson 8 - Machine Learning with Python (Scikit–Learn)

  • 8.1 Introduction to Machine Learning
  • 8.2 Machine Learning Approach
  • 8.3 How Supervised and Unsupervised Learning Models Work
  • 8.4 Scikit-Learn
  • 8.5 Supervised Learning Models - Linear Regression, Logistic Regression
  • 8.6 K Nearest Neighbors (K-NN) Model
  • 8.7 Unsupervised Learning Models: Clustering, Dimensionality Reduction
  • 8.8 Pipeline  Model Persistence  Model Evaluation - Metric Functions

Lesson 9 - Natural Language Processing with Scikit-Learn

  • 9.1 NLP Overview
  • 9.2 NLP Approach for Text Data
  • 9.3 NLP Environment Setup
  • 9.4 NLP Sentence analysis  NLP Applications
  • 9.5 Major NLP Libraries  Scikit-Learn Approach
  • 9.6 Scikit - Learn Approach Built - in Modules  Scikit - Learn Approach Feature Extraction
  • 9.7 Bag of Words  Extraction Considerations
  • 9.8 Scikit - Learn Approach Model Training
  • 9.9 Scikit - Learn Grid Search and Multiple Parameters
  • 9.10 Pipeline

Lesson 10 - Data Visualization in Python using Matplotlib

  • 10.1 Introduction to Data Visualization
  • 10.2 Python Libraries  Plots
  • 10.3 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
  • 10.4 Types of Plots and Seaborn

Lesson 11 - Data Science with Python Web Scraping

  • 11.1 Web Scraping
  • 11.2 Common Data/Page Formats on The Web
  • 11.3 The Parser  Importance of Objects
  • 11.4 Understanding the Tree  Searching the Tree
  • 11.5 Navigating options  Modifying the Tree
  • 11.6 Parsing Only Part of the Document
  • 11.7 Printing and Formatting  Encoding

Lesson 12 - Python integration with Hadoop, MapReduce and Spark

  • 12.1 Need for Integrating Python with Hadoop
  • 12.2 Big Data Hadoop Architecture
  • 12.3 MapReduce  Cloudera QuickStart VM Set Up
  • 12.4 Apache Spark
  • 12.5 Resilient Distributed Systems (RDD)
  • 12.6 PySpark  Spark Tools
  • 12.7 PySpark Integration with Jupyter Notebook

Exam Certification

Python Online Training Course is intended for clearing the IgmGuru Python Certification exam. The whole training course content is intended by business professionals to induce the most effective jobs within the high MNCs. As a part of this coaching, you may be engaged on real-time projects and assignments that have large implications within the real world business situation so serving to you way your career effortlessly.

At the tip of this educational program, there'll be quizzes that completely replicate the kind of queries asked within the various certification examinations and helps you score higher marks within the certification exam.

IgmGuru Course Completion Certification is awarded on the completion of Project work (on skilled review).

Frequently Asked Questions

A :No, Exam expense is excluded in the preparation charges.

A :IgmGuru provides the course completion certificate, after clear the exam.

A :We offer day in and day out help through email, talk, and calls. we have a tendency to try and have an energetic group that gives on-request help through our locale discussion. What's a great deal of, you may have life expectancy access to the network gathering, even once fruition of your course with us.

A :Our instructing collaborators are an over the top group of material experts here to help you to get ensured in your underlying attempt. They have communication with understudies proactively to affirm the course way is being pursued and help you to advance your learning ability, from classification onboarding to extend tutoring and work help. Training help is open all through business hours.

A :All of our to a great degree qualified mentors are AWS ensured with long stretches of ability instructing and managing inside the cloud space. everything about has had a thorough decision strategy that has profile screening, specialized examination, and an instructing demo before they're ensured to mentor for us. we tend to conjointly ensure that exclusively those mentors with a high graduated class rating remain on our personnel.

A :The devices you'll have to go to preparing are • Windows: Windows XP SP3 or higher • Mac: OSX 10.6 or higher • Internet speed: Preferably 512 Kbps or higher Headset, speakers, and amplifier: You'll require earphones or speakers to hear guidance obviously, and also a mouthpiece to converse with others. You can utilize a headset with an implicit amplifier, or separate speakers and mouthpiece.

A :All of the classifications square measure led through live on-line spilling. they're intuitive sessions that adjust you to bring inquiries and take an interest up in discourses all through classification time. We do, in any case, offer chronicles of each session you go to for your future reference. classes square measure gone to by a world group of onlookers to supplement your learning aptitude.

Data Science With Python

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