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Python Certification Training for Data Science ( L057 )

4.5 + (25,859) Students Ratings

IQ Training’s Python for Data Science Training will enable you to master the concepts of data science from scratch. This course will help you to gain in-depth knowledge on the python programming concepts such as data analysis, file operations, OOPs concepts, and various python libraries which are very much essential for Data science. Upon completion of this course, you will master the important tools of Data science with python.

Course Price :

₹22,765
₹25,294
10%
off
Available

Live Instructor

Self Paced

Think Bigger Advantage

Live Online Classes

All our Classes are Live Instrucotor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schdules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of Completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Training Scheule
Batch Start Date Days of Training Weekday/ Weekend Timings
14-Mar-2020 Available SAT & SUN (7 WEEKS) Weekend Batch 11:00 AM - 02:00 PM (EST)
23-Mar-2020 Available MON-FRI (21 DAYS) Weekday 11:00 AM - 01:00 PM (EST)
27-Mar-2020 Available SAT & SUN (7 WEEKS) Weekend Batch 09:30 PM - 12:30 AM (EST)
03-Apr-2020 Available SAT & SUN (7 WEEKS) Weekend Batch 09:30 PM - 12:30 AM (EST)
19-Apr-2020 Available MON-FRI (21 DAYS) Weekday 09:30 PM - 11:30 PM (EST)
 
 
 
 
 

Course Curriculum

Learning Objectives: In this module, you will learn the basics of python.

Topics:

  • Python Overview
  • Different Applications where Python is used
  • Understand Python Scripts on UNIX/Windows
  • Values, Types, Variables
  • Operands and Expressions
  • Conditional Statements and loops
  • Command Line Arguments
  • Writing to the screen

Skills:

  • Python programming Fundamentals

Learning Objectives: In this module, you will understand the different types of sequence structures, related operations and their usage. By the end of this module, you will learn to read and write files. 

Topics:

  • Python files I/O Functions
  • Numbers
  • Strings, Tuples, lists , dictionaries, sets and their related operations

Skills:

  • File Operations using Python
  • Working with data types of Python

Learning Objectives: This module helps you to create generic python scripts. By the end of this module you will be able to address errors/exceptions in code and learn to extract/filter content using regex.

Topics:

  • Functions and its parameters
  • Global Variables
  • Variable Scope and Returning Values
  • Lambda Functions
  • OOPs Concepts
  • Standard Libraries
  • Modules in Python
  • The Import Statements
  • Module Search Path
  • Installation Ways of Package 
  • Handling Errors and Exceptions 

Skills:

  • Error and Exception handling management in Python
  • Working with functions in Python

Learning Objectives: This module deals with the basics of statistics, types of measures, probability distributions, supporting libraries in python. By the end of this module, you will learn about data visualization.

Topics:

  • NumPy - arrays
  • Operations on arrays
  • Indexing, slicing and iterating
  • Reading and writing arrays on files
  • Data structures & index operations of Pandas
  • Reading and Writing data into Pandas from excel/csv formats
  • matplotlib library
  • Grids, axes, plots
  • Markers, colours, fonts and styling
  • Types of plots - bar graphs, pie charts, histograms
  • Contour plots

Skills:

  • Probability Distributions in Python
  • Data Visualization

Learning Objective: In this module, you will understand in detail about Data Manipulation. 

Topics:

  • Basic Functionalities of a data object
  • Merging and Concatenation of Data objects
  • Types of Joins on data objects
  • Exploring and Analysing a Dataset

Skills:

  • Python in Data Manipulation

Learning Objectives: This module will help you to understand the concepts of Machine Learning and its types. 

 

Topics:

  • Python Revision (numpy, Pandas, scikit learn, matplotlib)
  • What is Machine Learning?
  • Machine Learning Use-Cases. Process Flow and Categories
  • Linear regression
  • Gradient descent

  Skills:

  • Machine Learning concepts and types
  • Linear Regression Implementation

Learning Objectives: This module helps you understand the supervised techniques and their implementation. 

 

Topics:

  • Classification and its use cases
  • What is Decision Tree and Algorithm for Decision Tree Induction
  • Creation of a Perfect Decision Tree
  • Confusion Matrix
  • What is Random Forest?

Skills:

  • Supervised Learning concepts and implementation of different types of Supervised Learning algorithms
  • Evaluating model output

Learning Objectives: In this module you will be taught about the impact of dimensions with in data. By using PCA and compress dimensions, you will be taught to perform factor analysis and develop LDA model. 

 

Topics:

  • Dimensionality Introduction
  • Why Dimensionality Reduction
  • PCA
  • Factor Analysis
  • Scaling dimensional model
  • LDA

Skills:

  • Dimensionality Reduction Technique Implementation

Learning Objectives: This module will help you to discuss about the techniques of supervised learning. You will also understand how to implement those techniques. for example, Decision Trees, Random Forest Classifier etc. 

 

Topics:

  • What is Naïve Bayes and how it works?
  • Implementation of Naïve Bayes Classifier
  • What is Support Vector Machine and how it works?
  • Hyperparameter Optimization
  • Grid Search vs Random Search
  • Support Vector Machine Implementation for Classification

Skills:

  • Concepts of Supervised Learning 
  • Implementing different types of Supervised Learning algorithms
  • Evaluating model output

Learning Objectives: This module deals with Unsupervised Learning and the various types of clustering for analysing the data. 

 

Topics:

  • What is Clustering & its Use Cases?
  • What is K-means Clustering? How does it work?
  • How to do optimal clustering
  • What is C-means Clustering and Hierarchical Clustering?
  • Working of Hierarchical Clustering

Skills:

  • Unsupervised Learning
  • Implementation of Various types of Clustering

Learning Objectives: This module will teach you the Association rules and their extension towards recommendation engines with Apriori algorithm. 

 

Topics:

  • What are Association Rules and their Parameters
  • Association Rule Parameters and its calculations
  • What is Recommendation Engine? How it works?
  • Collaborative Filtering and Content-Based Filtering

 

Skills:

  • Data Mining and Recommender system using python

Learning Objectives: This module will help you to develop smart learning algorithm that is used for accurate learning. Based on agent-environment interaction, you will be able to define an optimal solution. 

Topics:

  • What is Reinforcement Learning and its use
  • Elements of Reinforcement Learning
  • Exploration vs Exploitation dilemma
  • Epsilon Greedy Algorithm
  • Markov Decision Process (MDP)
  • Q values and V values
  • Q – Learning
  • α values

Skills:

  • Implement Reinforcement Learning and Q learning using python

Learning Objectives: In this module, deals with time series analysis to forecast dependent variables based on time. You will learn different models for time series modeling such that you will analyze a real time-dependent data for forecasting.. 

 

Topics:

  • What is Time Series Analysis and its importance
  • Components of TSA
  • White Noise
  • AR and MA model
  • ARMA and ARIMA model
  • Stationarity
  • ACF & PACF

 Skills:

  • Time Series Analysis in Python

Learning Objectives: In this module, you will learn Model selection and its importance. You will also learn about Boosting and the importance of Machine Learning. By the end of this module, you will learn to convert weaker algorithms into stronger ones. 

Topics:

  • What is Model Selection and its need?
  • Cross-Validation
  • What is Boosting and How Boosting Algorithm works?
  • Types of Boosting Algorithms
  • Adaptive Boosting

Skills:

  • Model Selection
  • Boosting algorithm using python
Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Course Details

After completing this Data Science training, you will be able to:

  • Download and analyze data
  • Understand different techniques to deal with different types of data
  • Learn data visualization
  • Master the art of presenting step by step data analysis by using I python notebooks 
  • Understand the roles of Machine Learning Engineer
  • Describe Machine Learning
  • Work with real-time data
  • Understand tools and techniques for predictive modeling
  • Learn Machine Learning algorithms and their implementation
  • Validate Machine Learning algorithms
  • Explain Time Series and its related concepts
  • Perform Text Mining and Sentiment analysis

The Following professional can choose Data Science certification course in Python 

  • Developers who are aspiring to be a Machine Learning Engineer
  • Technical Leads
  • Architects
  • Analytics Managers
  • Business Analysts who aspire to understand Machine Learning (ML) Techniques
  • Information Architects who wish to get expertise in Predictive Analytics
  • 'Python' professionals 

The following are the pre-requisites for Python course include 

  • Basic understanding of Programming Languages. 
  • Fundamentals of Data Analysis with related tools

However, IQ Online provide a complimentary “Python Statistics for Data Science” self paced course for all the enrollers

Python Certification Training for Data Science Ceritficate

Python Certification Training for Data Science Reviews

25,859

Total number of reviews

4.5

Aggregate review score

80%

Course completion rate

Python Certification Training for Data Science Features

Live Online Classes

All our Classes are Live Instructor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schedules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Course Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Python Certification Training for Data Science FAQs

You will never miss a class at IQ Online Training! You can choose either of the two options:

  1. View the recorded session of the class available in your LMS or
  2. You can attend the missed session in any other live batch.

After the enrolment, the LMS access will be instantly provided to you able to access for lifetime which includes complete set of previous class recordings/PPTs/PDFs/assignments. You can start learning right away.

Your access to the Support Team is for lifetime. Our team will help you in resolving queries, during and after the course.

Yes, once enrollment has done for course. Access to the course material will be available for lifetime.

You can Call our support numbers listed in site OR Email us at info@iqtrainings.com.

You can view in-depth class sample recordings before the enrollment. Experience the complete learning instead of a demo session with our expertise.

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

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