Python certification training

Python certification training
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ProIct's Python course helps you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scikit and master the concepts like Python Machine Learning Algorithms such as Regression, Clustering, Decision Trees, Random Forest, Naïve Bayes and Q-Learning and Time Series. Throughout the Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR and so on.


Objectives

After completing this module, you should be able to:

Understand Python basic concepts

Understand scripting concepts

Distinguish Programming language and scripting language

 

Topics:

Get an overview of Python

The companies using Python

Other applications in which Python can be used

Explore Python Frameworks and IDEs  

Concept of Scripting 

Difference between Scripting language and Programming language

Installation of Python

Versions of Python

 

 

Hands-on/Demo

Create “Hello world” code

 

Objectives
After completing this module, you should be able to:
Define Reserved Keywords and Command Line Arguments
Understand data types
Execute decision-making statements 
Use Loops
 
Topics:
Introduction to Identifiers
What are the different variable types?
Different operators
Decision making statements
Loops 
 
Hands-on/Demo
Data types - string, numbers
Keywords
Variables
Demonstrating decision making statements
Demonstrating Loops
 

Objectives
After completing this module, you should be able to:
Explain Numbers 
Explain Strings, Tuples, Lists, Dictionaries, and Sets
 
 
Topics: 
Numbers
Strings and related operations
Tuples and related operations
Lists and related operations
Dictionaries and related operations
Sets and related operations
 
Hands-on/Demo
Tuple - properties, related operations, comparison with list
List - properties, related operations
Dictionary - properties, related operations
Set - properties, related operations
 

Objectives
After completing this module, you should be able to:
Take input from user with the help of Pycharm and perform operations on it
Create and execute functions
Define Modules (Boto3)
Handle the exceptions
Explain Standard Library
 
 
Topics: 
Python files I/O Functions
Function Parameters
Global variables
Variable scope and Returning Values
Modules used in python
Python Boto ec2 module
Errors and Exception Handling
Handling multiple exceptions
The standard exception hierarchy Using Modules
 
 
Hands-on/Demo
Functions - syntax, arguments, keyword arguments, return values
Errors and exceptions - types of issues, remediation
Packages and module - modules, import options, sys path
 

Objectives
After completing this module, you should be able to:
Understand the concept of Database
Access MySQL DB 
Create socket for sending short messages
Create GUI
 
Topics:
Why Python is called Object oriented language?
Class and Objects
MySQL DB access
Network programming
Multithreading
GUI programming
 
Hands-on/Demo
Network Creation
Create GUI

Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing. 
 
ProICT's Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds. 
 
Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to train your machine based on real-life scenarios using Machine Learning Algorithms.
 
ProICT’s Python course will also cover both basic and advanced concepts of Python like writing Python scripts, sequence and file operations in Python. You will use libraries like pandas, numpy, matplotlib, scikit, and master the concepts like Python machine learning, scripts, and sequence.
 

It's continued to be a favourite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python cuts development time in half   with its simple to read syntax and easy compilation feature. Debugging programs is a breeze in Python with its built in debugger. 

It runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.

It has evolved as the most preferred Language for Data Analytics and the increasing search trends on Python also indicates that it is the " Next Big Thing " and a must for Professionals in the Data Analytics domain.

Read more on Top 10 reasons to learn Python

After completing this Data Science Certification training, you will be able to:
 
  • Programmatically download and analyze data
  • Learn techniques to deal with different types of data – ordinal, categorical, encoding
  • Learn data visualization
  • Using I python notebooks, master the art of presenting step by step data analysis
  • Gain insight into the 'Roles' played by a Machine Learning Engineer
  • Describe Machine Learning
  • Work with real-time data
  • Learn tools and techniques for predictive modeling
  • Discuss Machine Learning algorithms and their implementation
  • Validate Machine Learning algorithms
  • Explain Time Series and its related concepts
  • Perform Text Mining and Sentimental analysis
  • Gain expertise to handle business in future, living the present

ProICT’s Data Science certification course in Python is a good fit for the below professionals:
 
  • Programmers, Developers, Technical Leads, Architects
  • Developers aspiring to be a ‘Machine Learning Engineer'
  • Analytics Managers who are leading a team of analysts
  • Business Analysts who want to understand Machine Learning (ML) Techniques
  • Information Architects who want to gain expertise in Predictive Analytics
  • 'Python' professionals who want to design automatic predictive models

The pre-requisites for ProICT's Python course include the basic understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, you will be provided with complimentary “Python Statistics for Data Science” as a self-paced course once you enroll for the course.

You will do your Assignments/Case Studies using Jupyter Notebook that is already installed on your Cloud Lab environment whose access details will be available on your LMS. You will be accessing your Cloud Lab environment from a browser. For any doubt, the 24*7 support team will promptly assist you.

CloudLab is a cloud-based Jupyter Notebook which is pre-installed with Python packages on the cloud-lab environment. It is offered by ProICT as a part of Python Certification Course where you can execute all the in-class demos and work on real-life projects in a fluent manner.
 
You’ll be able to access the CloudLab via your browser which requires minimal hardware configuration. In case, you get stuck in any step, our support ninja team is ready to assist 24x7.

This course comprises of 40 case studies that will enrich your learning experience. In addition, we also have 4 Projects that will enhance your implementation skills. Below are few case studies, which are part of this course:
 
Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its 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 plant family. They have asked us to automate this process and remove any manual intervention from this process.
 
You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference.
 
 
Case Study 2: BookRent 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 user rents more books. 
 
You as an ML expert and must model recommendation engine so that user gets a recommendation of books based on the behavior of similar users. This will ensure that users are renting books based on their individual taste. 
The company is still unprofitable and is looking to improve both revenue and profit. Compare the Error using two approaches – User Based Vs  Item Based
 
 
Case Study 3:  Handle missing values and fit a decision tree and compare its accuracy with random forest classifier.
 
Predict the survival of a horse based on various observed medical conditions. Load the data from ‘horses.csv’ and observe whether it contains missing values. Replace the missing values by the most frequent value in each column. Fit a decision tree classifier and observe the accuracy. Fit a random forest classifier and observe the accuracy.
 
Case Study 4:  Principal component analysis using scikit learn.
             
Load the digits dataset from sklearn and write a helper function to plot the image. Fit a logistic regression model and observe the accuracy.
Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Compare it with a model and also comment on the accuracy. Compute the confusion matrix and count the number of instances that have gone wrong. For each of the wrong sample, plot the digit along with the predicted and original label.
 
Case Study 5:  Read the datafile “letterCG.data” and set all the numerical attributes as features. Split the data in to train and test sets. 
 
Fit a sequence of AdaBoostClassifier with varying number of weak learners ranging from 1 to 16, keeping the max_depth as 1. Plot the accuracy on the test set against the number of weak learners, using decision tree classifier as the base classifier.
 

Project #1:

Industry: Social Media

Problem Statement: You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters.

Actions to be performed:

Load the corresponding dataset. Perform data wrangling, visualization of the data and detect the outliers, if any. Use the plotly library in Python to draw useful insights out of data. Perform regression modeling on the dataset as well as decision tree regressor to achieve your Learning Objectives. Also, use scaling processes, PCA along with boosting techniques to optimize your model to the fullest.

 

Project #2: 

Industry: FMCG

Problem Statement: You as an ML expert have to cluster the countries based on various sales data provided to you across years.

Actions to be performed:

You have to apply an unsupervised learning technique like K means or Hierarchical clustering so as to get the final solution. But before that, you have to bring the exports (in tons) of all countries down to the same scale across years. Plus, as this solution needs to be repeatable you will have to do PCA so as to get the principal components which explain the max variance.

You will never miss a lecture at ProICT! You can choose either of the two options:
  • View the recorded session of the class available in your LMS.
  • You can attend the missed session, in any other live batch.

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight into how are the classes conducted, quality of instructors and the level of interaction in a class.

All the instructors at ProICT! are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by ProICT for providing an awesome learning experience to the participants.

You no longer need a credit history or a credit card to purchase this course. Using ZestMoney, we allow you to complete your payment with a EMI plan that best suits you. It's a simple 3 step procedure:
  • Fill your profile: Complete your profile with Aadhaar, PAN and employment details.
  • Verify your account: Get your account verified using netbanking, ekyc or uploading documents
  • Activate your loan: Setup automatic repayment using NACH to activate your loan