(All course fees are in USD)

Course Description

Through this Python for Data Science training, you will gain knowledge in data analysis, machine learning, data visualization, web scraping, & natural language processing.  You will also get equipped to master the essential tools of Data Science with Python

Offered in Partnership with

Simplilearn

Course Delivery

• Online pre-recorded self-paced learning (24 hours)
• Live virtual classroom training (44 hours).

Total online blended learning: 68 hours

Benefits

• Data Science is an evolving field and Python has become a required skill for significant portion of jobs in Data Science.
• 68 hours of blended learning (24 hours online self-paced learning + 44 hours of instructor-led online training by industry experts)
• 4 industry-based projects
• Interactive learning with Jupyter notebooks labs
• 1 year access

Award upon Successful Completion

Data Science with Python Certificate of Achievement

Awarding Organisation

Simplilearn

Learning Outcomes

• Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics
• Understand the essential concepts of Python programming such as datatypes, tuples, lists, dicts, basic operators, and functions
• Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions
• Perform data analysis and manipulation using data structures and tools provided in the Pandas package
• Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline
• Use the Scikit-Learn package for natural language processing and matplotlib library of Python for data visualization

Assessments 

Fulfilling ALL of below:

• A score of at least 75% in course-end assessment, AND below:
• Complete 85% of the course
• Submit at least one completed project, with satisfactory evaluation by instructor.

Course End Projects

Project 1: Products rating prediction for Amazon

Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews of similar products.

Amazon would like to improve this recommendation engine by predicting ratings for the nonrated products and add to recommendations accordingly.

Domain: E-commerce

Project 2: Demand Forecasting for Walmart

Predict accurate sales for 45 stores of Walmart, a US-based leading retail stores, considering impact of promotional markdown events. Check if macroeconomic factors, such as CPI and unemployment rate, have an impact on sales.
Domain: Retail

Project 3: Improving Customer Experience for Comcast

Comcast, one of the largest US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction. The company is also looking for  recommendations to achieve satisfactory customer experience.

Domain: Telecom

Project 4: Attrition Analysis for IBM

IBM, one of the leading US-based IT companies, would like to identify factors that influence attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not.

Domain: Workforce Analytics

Project 5: NYC 311 Service Request Analysis

Perform a service request data analysis of New York City 311 calls. You will focus on data wrangling techniques to understand patterns in data and visualize major complaint types.

Domain: Telecommunication

Project 6: MovieLens Dataset Analysis

The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in several research projects in the fields of information filtering, collaborative filtering, and recommender systems. Here,  you  are to perform an analysis using the exploratory data analysis (EDA) technique for user datasets.

Domain: Engineering

Who Should Enrol

• Analytics professionals willing to work with Python
• Software and IT professionals interested in analytics
• Anyone with a genuine interest in data science

Prerequisites

This Python for Data Science training is beneficial for analytics professionals willing to work with Python, Software, and IT professionals interested in the field of analytics, and anyone with a genuine interest in Data Science.

To best understand the Data Science with Python course, it is recommended that you begin with these courses:

• Python Basics
• Math Refresher
• Data Science in Real Life
• Statistics Essentials for Data Science

Course Overview

Lesson 01 -Course Introduction

Lesson 02 – Introduction to Data Science

Lesson 03 – Python Libraries for Data Science

Lesson 04 – Data Wrangling

Lesson 05 – Feature Engineering

Lesson 06 – Exploratory Data Analysis

Lesson 07 – Feature Selection

Accessible Period of Course

1 year from date of enrolment

Customer Reviews

It was a great learning experience. My trainer, Vaishali delivered each session well. All topics were explained with in-depth theory, real-time examples, and execution of the same in Python. Her teaching methodology enhanced the learning process.

The online classes were well-paced and helped us learn a ton of stuff within a short amount of time. Vaishali is very knowledgeable and handled all the sessions with outstanding professionalism. Thanks for your expertise

I learned a lot about Python, Numpy, Pandas, Visualization. The instructor, Swagat was excellent in explaining things clearly. The support team is also accommodative and resolves issues instantly.

….. The faculty, Prashanth Nair, was extremely knowledgeable, and the entire class appreciated his way of teaching…..Support team was very accommodating and quick in providing responses. I was able to grab a 30% hike in my salary after getting certified.

The sessions are very interesting and easy to understand. I enjoyed each and every one of them, thanks to the trainer, Prashant

….. a brilliant platform to acquire new & relevant skills at ease. Well laid out course content and expert faculty ensure an excellent learning experience.

The instructor is knowledgeable and shares their skills and knowledge. My learning experience has been outstanding with Simplilearn. The practice labs and materials are helpful for better learning. Thank you, Simplilearn. Happy Learning!!

….. an excellent platform for online learning. Their course curriculum is comprehensive and up to date. We get lifetime access to the recorded sessions in case we need to refresh our understanding. If you are looking to upskill….

Incredible mentorship, and amazing and unique lectures. …..provides a great way to learn with self-paced videos and recordings of online sessions. …..

Prashant Nair is an awesome faculty. The way he simplifies, relates and explains topics is outstanding. I would love to enroll for and attend all his classes.

The instructor not only delivers the lecture but also focuses on practical aspects related to the subject. This is something about the course that really impressed me.

Thanks a lot, Sunny, for the immense support and guidance throughout the project, and for your patience while calmly helping me fix both small and big problems. You have excellent and in-depth knowledge about Python and the alternative options you taught me. I’m delighted to share my opinion about my experience.

……courses are affordable and helped me learn something new during the lockdown. Moreover, I also got to add a Well-Known Global Name like Simplilearn to my resume. I could choose the trainer as well as enroll for multiple sessions using the Flexible Pass.