Python Certification Training

Python Certification Training

Overview

Online education/course platform Edureka is organizing an online Python Certification Training for Data Science This is 7-week training program on data science There are various batches where you can enroll for this.

 

Topics

The topics which will be covered in this program are not limited to

  • Introduction to Python
  • Sequences and File Operations
  • Deep Dive – Functions, OOPs, Modules, Errors and Exceptions
  • Introduction to NumPy, Pandas, and Matplotlib
  • Data Manipulation
  • Introduction to Machine Learning with Python
  • Supervised Learning - I
  • Dimensionality Reduction
  • Supervised Learning - II
  • Unsupervised Learning
  • Association Rules Mining and Recommendation Systems
  • Reinforcement Learning
  • Time Series Analysis
  • Model Selection and Boosting

 

Batches

AUG29th SAT & SUN (7 WEEKS) Timings - 07:00 AM to 10:00 AM (IST)
SEP 14th 
MON - FRI (21 DAYS)
Timings - 08:30 PM to 10:30 PM (IST)
SEP 19 th 
SAT & SUN (7 WEEKS)
Timings - 08:30 PM to 11:30 PM (IST)
SEP 28th 
MON - FRI (21 DAYS)
Timings - 07:00 AM to 09:00 AM (IST)

 

 

Project

  • Maple Leaves Ltd is a start-up company that makes herbs from different types of plants and leaves. Currently, the system they use to classify the trees which they import in a batch is quite manual. A laborer from his experience decides the leaf type and subtype of the plant family. They have asked us to automate this process and remove any manual intervention from this process.
  • BookRenter is the largest online and offline book rental chain in India.  The company charges a fixed fee per month plus rental per book. So, the company makes more money when the user rents more books.
  • Handle missing values and fit a decision tree and compare its accuracy with a random forest classifier.
  • Principal component analysis using scikit learn.
  • Read the data file “letterCG.data” and set all the numerical attributes as features. Split the data into train and test sets. 

 

How to apply

Interested candidates can enroll in this course by the following link

 

How to apply Apply Here


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