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Data Science in Action using Python

Gain hands-on experience in building a Data Driven AI engagement using Python
5.0
5.0/5
(5 reviews)
62 students
Created by Neena Sathi

9.8

CourseMarks Score®

10.0

Freshness

9.5

Feedback

9.4

Content

Platform: Udemy
Price: $11.99
Video: 7h 28m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

9.8 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 4/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

9.5 / 10
We analyzed factors such as the rating (5.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.4 / 10
Video Score: 8.7 / 10
The course includes 7h 28m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
42 resources.
0 exercise.
0 test.

Table of contents

Description

With explosive growth of data in unstructured data, we have ample opportunities to design, develop and deploy AI models. While there are many courses which teach you Data Science, you need a step-by-step guide on how to select a problem, explore data, develop and deploy models and improve the model using user feedback and learning. This course covers many big data challenges and modifies CRISP-DM to deal with big data. This course provides you a methodology for AI model development and deployment as modified by us to deal with AI and big data. Our modifications have been tried on a number of real-life large-scale projects. We will select a real case study for this data science project and will provide hands-on experience in Designing / prototyping a Data science engagement on the chosen case study. You will be able to use the results in your day-to-day life.
We divide the data scientists into clickers and coders. Clickers are those data scientists who use a data science tool with a user interface to provide a high-level specification. Examples include SPSS Modeler, Excel and Alteryx. In each case you can add formula, but do not need to write code. The second set of data scientists are those who use a procedural language with libraries to write code for data science work. Python is the most popular language among data scientists. The objective of this course is to get you an introductory coding experience in data science. If you are interested in a clicker course, we offer a course using Alteryx for exactly the same content.  In addition, Our data science methodology course is also designed for Business Analysts and Project Managers with limited development background.
Course starts with two critical activities
•Set up Environment – step by step instructions in preparing sandbox environment for executing all your python code
•Data Science Methodology – to review key steps, tasks and activities associated with our data science methodology
After above section, This course introduces our 7 step data science methodology and use Python to explain each step using our real life use case example . These 7 steps include
•Step 1: Describe Use Case to explain selected use case for data science work
•Step 2: Describe Data to describe Data Sources and explain data sets using Python as a language.
•Step 3: Prepare Datasets to Prepare Data Sets using Python
•Step 4: Develop Model will provide hands-on exercises in applying many AI modeling techniques on data sets such as time series analysis, classification, clustering, regression, and forecasting,. All these exercises will be using Python as a language.
•Step 5: Evaluate Model will provide measurements to Evaluate your AI Model Results
•Step 6: Deploy Model will provide process for deploying your AI models.
•Step 7: Monitor model will provide process for continuous monitoring and evaluating your models in production
In this course, we will give you an opportunity to design a use case and then work on its implementation using Python as your primary language. You should download all data sets and sample python code. Complete all assignment in each section of the course and submit your final notebook using instructions provided.

Requirements

• There is no pre-requisites for this course. Knowledge of Python desired but not required
• We will teach elementary Python and Scikit-Learn and will provide recommendations for advanced Python learning

You will learn

✓ Students will learn proven modified CRISP-DM methodology to deal with big data challenges as we move from BI world to AI world
✓ Students will use real case study for this data science project and will gain hands-on experience in Designing / prototyping a Data science engagement on the chosen case study. You will be able to use the results in your day-to-day life.
✓ We divide the data scientists into clickers and coders. Clickers Examples include SPSS Modeler, Excel and Alteryx. This course is for coders not Clickers. For clickers we have designed similar courses like “Data Science Methodology” and “Data Science in Action using Alteryx”
✓ This course is designed for data scientists and data engineers who use a procedural language with libraries to write code for data science work. This course uses Python to show all necessary steps and activities needed for successful data science engagement.

This course is for

• This course is for anyone interested in becoming a data scientist such as Students, Business Analysts, Developers Testing professionals
• There are four possible careers where this course can be used as introductory material such as data scientists, AI or automation engineer, test engineers and finally knowledge engineers

How much does the Data Science in Action using Python course cost? Is it worth it?

The course costs $11.99. And currently there is a 87% discount on the original price of the course, which was $94.99. So you save $83 if you enroll the course now.

Does the Data Science in Action using Python course have a money back guarantee or refund policy?

YES, Data Science in Action using Python has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Data Science in Action using Python course, but there is a $83 discount from the original price ($94.99). So the current price is just $11.99.

Who is the instructor? Is Neena Sathi a SCAM or a TRUSTED instructor?

Neena Sathi has created 8 courses that got 47 reviews which are generally positive. Neena Sathi has taught 205 students and received a 4.1 average review out of 47 reviews. Depending on the information available, Neena Sathi is a TRUSTED instructor.

More info about the instructor, Neena Sathi

Principal, Applied AI Institute
Neena Sathi is a principal at Applied AI Institute. She has 30+ years of experience envisioning, designing, developing and implementing AI solutions associated with enhancing customer experience, back office automation and risk and compliance for many Fortune 100 organizations. She has worked in senior technical positions at Carnegie Group, Inc, an AI startup, Accenture, KPMG, and IBM.Neena has three masters degrees including MBA from leading US universities. She is Master certified integration architect from IBM and Open Group as well as certified Project management professional (PMP) from Project management institute. She is also certified in many Cloud and Cognitive technologies. She has widely presented and published many papers in AAAI, IEEE, WCF, ECF, IBM Information on Demand, IBM Insight, World of Watson, IBM Developer Works and various academic journals.

9.8

CourseMarks Score®

10.0

Freshness

9.5

Feedback

9.4

Content

Platform: Udemy
Price: $11.99
Video: 7h 28m
Language: English
Next start: On Demand

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