Workshop on Python with Machine Learning

7-8 days

Module 0:

Why Python?                                                                                                                                           

  • How would Python be useful?
  • Python in Analytics

Module 1:

Setting up your machine                                                                                                                     

  • Download Anaconda from Continum.io
  • How to use IPython Notebook

Module 2:

Basics of Python language                                                                                                                 

  • Understand the basics of the language, libraries & data structure
  • Understand classes & objects

Module 3:

Regular Expressions in Python                                                                                                            

  • Strings & Console output
  • Date & Time
  • Use RE for cleansing text data.

Module 4:

Conditionals & Control Flow                                                                                                                 

  • Syntax
  • Create programs to generate different outcomes based on user input

Module 5:

Functions                                                                                                                                                       

  • Write functions to reuse your code

Module 6:

Lists & Dictionaries                                                                                                                              

  • Use lists & dictionaries to store, organize & manipulate information

Module 7:

Lists & Functions combined                                                                                                                 

  • Get hands on with functions, lists & conditionals

Module 8:

Loops & Operators                                                                                                                              

  • While
  • For
  • Introduction to Bitwise operators

Module 9:

Scientific libraries in Python – NumPy, SciPy, Matplotlib  & Pandas                              

  • Importing Data
  • Exploratory data analysis with Pandas
  • Data munging & cleaning
  • Imputing Data
  • Aggregation & Grouping

Module 10:

Effective Data Visualization                                                                                                            

  • Do’s & Don’t of Visualization
  • How to make effective Charts

Module 11:

Scikit-learn & Machine Learning                                                                                              

  • Brief overview of the library                                                                                          
  • Overview of Machine Learning                                                                                          
    • What is Machine Learning
    • History and it’s Evolution
  • Types of Machine Learning                                                                                
    • Supervised Machine Learning
    • Unsupervised Machine Learning
  • Regression                                                                                                                             
    • Linear Regression
      • Assumptions
      • Fitting of model
      • Interpretation of Parameters & it’s tuning
    • Logistic Regression
      • Assumptions
      • Fitting of Model
      • Interpretation of Parameters & it’s tuning
  • Decision trees                                                                                                                      
    • Classification and Regression Trees (CART)
      • Building a decision tree
      • Pruning of decision trees
    • Random Forest
      • What is Random Forest?
      • Why you need Random Forest?
  • Clustering                                                                                                                                 
    • K-means Algorithm
    • When & how to use K-means?
  • Dimensionality reduction                                                                                            
    • Curse of Dimensionality
    • Principal Component Analysis(PCA)
  • Advanced Algorithms                                                                                                           
    • Support Vector Machines
  • Kernels
  • SVMs in Practice
  • Neural Networks
    • Motivation
    • Fitting a neural network
    • Classification using Neural nets
    • Parameter tuning
  • XG Boost and its Application
    • Classification using XGBoost
  • Features                                                                                                                                 
    • Feature Engineering
    • Feature Selection
    • Feature Scaling
  • Validation & Evaluation                                                                                              
    • Training/testing data split
    • Cross-Validation
    • Precision, Recall & F1 Score
  • Ensemble Methods                                                                                                                             
    • Why do we need Ensemble?
    • How to do Ensemble ?
      • Blending/Stacking

Module 12:

Case study                                                                                                                                                  

Module 13:

Resources for learning advanced topics in Python & Machine Learning                         

Module 14:

Q&A                                                                                                                                                         

The Workshop content consists of an approximately equal mixture of lecture and hands-on lab. 

Recommendation: It is strongly recommended to bring your own LAPTOP during the training on which you can install and run programs if you would like to do the optional, hands-on experiments/exercises after the trainings/ workshops.

Certificates will be provided by ISO 9001:2008 certified I-Medita Learning Solutions Pvt. Ltd. Company which is registered with Ministry of Corporate Affairs for providing IT Trainings all over India and IBNC India which is a trademark championship that has already been executed in 106 Engineering colleges till March 2015.

  • Participation Certificate: Given to each candidate who participate in the workshop
  • Appreciation Certificate: Given to the College/ Institution who help in conducting the workshop.
  • Excellence Certificate: Given to the winner of the Zonal Center Championship.
  • Coordination Certificate: Given to those active & strong students and faculty coordinators who help in making the workshop and training successful.

IBNC Team gives you freedom to ask your relationship manager at IBNC India for certificate samples in advance so that you could be aware of the certificate you will be receiving before hand the trainings/workshops.

IBNC DVD to each participant to help them learn more about the workshop containing e books, presentations, videos and softwares after the training.

  • One on one interaction in the class with the Trainer.
  • Study material designed by panel of experts from industry.
  • Lead trainer will also have supporting trainers with him/her so that they can help you fall in love with the technology.
  • We believe in learning with fun!
  • The skills we develop are those that employers within the industry are looking for.
  • Covering theoretical and practical concepts in such a way that it is fun to learn the technology and easy to make unique projects.
  • Your skills and certifications are recognized anywhere in the world your career takes you.
  • Successfully trained over 15000 students in India till now.
  • Watch video testimonials given by students: www.youtube.com/ibncindia
  • Check out our facebook page to see live comments from our prestigious students.
  • IBNC makes sure that you should get the full worth of the money you have paid during the trainings anywhere in India.

Please contact IBNC India Team to know more about careers in this technology.