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Machine Learning Using Python Training in Chicago-IL, United States

Learn how to arrive at lucrative business decisions by using Python and machine learning with ways to use Python packages to data analysis applications

  • 40 hours of Instructor led training
  • Basic to Intermediate level
  • In-depth hands-on classes
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Modes of Delivery

Key Features

40 hours of Instructor led sessions
Immersive hands-on training
Learn data processing & analysis with python and Hadoop
Learn to create accurate data science models and use Python libraries effectively
Understand how Python works in Hadoop distributed File System
Develop analytical apps with Python advanced concepts
Our experts will guide you in implementing M/L concepts for future projects

Description

Zeolearn academy brings you a comprehensive, hands-on introduction on Python basics and its use in data analytics.

Over the past few years, big data and its analysis have grown exponentially and changed the way businesses operate. Python has emerged as a strong contender for carrying out predictive analysis on Big Data, because of its syntax, clarity, and easy readability. This workshop focuses on how you can use Python to carry out data processing and analysis and arrive at complex computations by combining it with Hadoop. We assure you that Participants will learn extensively about Pandas, Matplotlib, Scipy and Numpy, and the IPython toolkit through a well-paced and informative coaching that places extensive emphasis on hands-on practical sessions from our Machine Learning with Python course. Our highly qualified and certified trainers bring their own experiences and style to the Machine Learning with Python training. The fee we are charging for Machine learning certification is affordable and course completion certificate will be issued on successful completion of course. Register today and get access for your class study materials.

Here’s what you will learn!

  • The importance of data analysis and why it so important in this age and time
  • How to predict future outcomes and arrive at lucrative business decisions by using Python and machine learning and applying predictive algorithms to data
  • How to create accurate data science models and use Python libraries such as Numpy, Scipy, and Matplotlib effectively
  • How Python works in the Hadoop distributed file ecosystem, PIG and Hive
  • To use Python packages for data analysis applications

Prerequisites:

Programmers with Python background will find this course beneficial.

Curriculum

  • Python installation
  • Data types in python
  • Basic operations and functions
  • Introducing numpy
  • Vector matrix arrays
  • Plotting and visualization
  • Numpy for pandas
  • Playing around pandas series
  • Playing around pandas data frame
  • Working on dataset In pandas
  • Combining reshaping data
  • Grouping and aggregating data
  • Definition of machine learning
  • Types of machine learning
  • Few examples on machine learning implementations
  • Machine learning: the problem setting
  • Loading an example dataset
  • Learning and predicting
  • Model persistence
  • Conventions
  • Data visualization using pandas
  • Using matplotlib
  • Using seaborn

Frequently Asked Questions

Data analysis is hot! It is a combination of different disciplines such as statistics, mathematics, computer science and machine learning and is used on data with the intention of arriving at useful insights and supporting business decision making. Data analysis has changed the way organizations operate and is applicable in a variety of fields from retail and healthcare to entertainment and hospitality. Python on the other hand is a multi-domain, high-level, programming language highly preferred for its easy readability, vast array of libraries and reliability. Python has emerged as the most convenient language for data analysis and machine learning. If you want to pursue a career in data analysis, then learning Python is a must as data analysis with Python has several advantages and is what organizations will use going forward. 

  • Advanced data structures and algorithms available in Scipy, Numpy and Pandas
  • Plotting using Matplotlib
  • Using Scipy, Numpy and Pandas for data modeling and analysis
  • Using the above libraries to create data frames, grouping, processing data and perform numerical and scientific analysis using Scipy, Numpy and Pandas
  • Creating classifiers, clusters
  • Strategies to deal with reducing dimensions, selecting appropriate data models
  • Using analytics libraries with Hadoop Map Reduce, PIG and HIVE

Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will use Python packages to perform data analysis with support from your mentors. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.

Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.

You may be required to put in 10 to 12 hours of effort every week, including the live class, self study and assignments.

Your classes will be held online. All you need is a windows computer with good internet connection to attend your classes online. A headset with microphone is recommended.

You may also attend these classes from your smart phone or tablet.

Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.

Web masters, Programmers, Professional Software Developers, Scientists, Analysts and Entrepreneurs and anyone who wishes to get in-depth knowledge of Python will find value in attending this course.

One must have:

  • Operating system such as Mac OS X, Windows or Linux
  • Good Text / JavaScript Editor (Notepad++ / SublimeText / Brackets / Atom )
  • A modern web browser such as Chrome
  • Internet Connection

Machine Learning with Python Course in Chicago-IL

Machine learning with Python


ZeoLearn, a registered institute which has numerous certified courses worldwide, offers Python Machine Learning Course in Chicago, the United States 40 hours of advanced online training offered by lecturers who have substantial experience in Python. Python Machine Learning training in Chicago throughout the week and students can enrol for any convenient class type based on their availability and facilities. Students who register for the Python Machine Learning online training in Chicago are expected to have known basic programming knowledge in Python. Students can easily enrol for this online course and must spend at least 10 to 12 hours of weekly timings for self-study, online classes and project completion. If any particular session is missed in this online training, students can refer to the class recordings or take up another live batch session of python machine learning course in Chicago.

What you Learn!
The Machine learning with python online classes in Chicago has a well-framed curriculum by Python experts. The modules of this workshop teach its students about Python setup, numerical computing using Python, Introduction to scipy, introduction to pandas, basics of machine learning, machine learning with sci-kit learn and data visualisation.

Students have to submit a project at the end of the python machine learning training in Chicago as a means to get familiar with all the concepts learnt in this online course. It is a live project working with Python packages to perform data analysis. Instructors and fields experts review it. Once approved, ZeoLearn offers python machine learning certification in Chicago.

Key Benefits of the Course and Academy


The python machine learning certification in Chicago is recognised in the field of data science and helps the students get a glittering career as a data analyst. ZeoLearn's mentor-driven courses not only teach them theory but also offers practice sessions, demos and real exposure. The key feature about ZeoLearn is that, unlike other academics, it provides the facility of staying in constant touch with the experts and follow up on the updating features and technologies in Python and data science.

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