Data Science A to Z Specialization Course

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    Anshu Pandey
  • 2360 (Registered)
  • (11 Reviews)

Data Science A to Z Specialization Course

Program Overview

Data Science with Python course will acquaint the participants with the nuts and bolts of the python programming condition and dataset including how to download and introduce python, expected basic python programming methods, and how to discover help with python programming questions. The course will likewise present information control and cleaning methods utilizing the famous python pandas information science library and present the reflection of the Data Frame as the focal information structure for information examination.


This course is part of multiple programs

This course can be applied to multiple Specializations or Professional programs. Completing this course will count towards your learning in any of the following programs



Basic of Mathematics and programming and no other prerequisite required to learn this course, we are gonna cover from basic to advanced.



Course Objective

  1. To make the learner identify potential zones of uses of Data Science.
  2. Providing experience in working with real-time applications of Data Science.
  3. Make a learner easily land up to a job role of either Data Scientist, Data Analyst, Business Analyst in IT Industry.



Course covers

Data Science A to Z is a bundle of multiple courses that will help you to learn step by step. please check the detail in the given Courses.







Download full Course Curriculum

Course Features

  • More than 80% hands-on session
  • Project-oriented learning
  • Cloud-based LMS
  • Experienced Trainer
  • Masterclass for Expert
  • Standard reading materials
  • Study resources
  • Graded Quizzes
  • Real-time case study-based projects
  • Discussion Forum


Capstone Projects

  1. Exploratory Data Analysis of USA Bachelors Dataset
  2. Exploratory Data Analysis on Hyderabad Air Traffic Dataset from data.gov.in
  3. Hypothesis testing on sales data, sales pattern extraction
  4. Exploratory Data Analysis of IPL Dataset
  5. Churn Prediction for an Enterprise
  6. Credit Card Fraud Detection
  7. Hypothesis testing on female literacy and fertility dataset, working with correlation analysis, visualizing the data.
  8. Fetching data related to the number of Pinterest accounts maintained by IS state Department and embassies and missions and performing Exploratory Data Analysis
  9. Social Media Data Analysis
  10. Predictive Analysis on Credit Default Dataset



Software & Tools details


Python ( Click Here for Download )

Anaconda for Python 3.x ( Click Here for Download ) and other miscellaneous software and tools




Course Outcome

Before the finish of this course you will:

  1. Have an astonishing arrangement of illustration python information investigation ventures!
  2. Have a comprehension of Machine Learning and SciKit Learn!
  3. The learner will be able to land up in a job role related to Data Analyst and Data Science.
  4. The Learner can also easily switch from existing job role with around of 20% hike from the current salary switch to any of the field where Data Science is being used.
  5. The learner will become capable of handling any project relevant to Data Science in a proper way.



Suggested Job Profile after taking this course

After completion of this course, a candidate can directly land upon the given profile, these are the world’s best job profiles.

  1. Data Scientist
  2. Data Analyst
  3. Business Analyst
  4. Data Science Associate
  5. Chief Data Scientist
  6. BI Professional
  7. R & D Professional and others


Machine Requirement

  1. Windows Machine (Windows 7 or Above) /Linux Machine
  2. Only 64 Bit
  3. 4 GB RAM (8 GB Recommended)



INR 20,000/- including all Tax and Services


60 Hours Hand On Training + 10 Hours Project Work

Mode of Training

Online Live Instructor-Led Class


Course Code- TTV/IND/00034

Upcoming Batch- 11th Jan 2021, 07:00 AM to 08:30 AM, IST (Monday & Friday)



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A Technical expert and a passionate trainer has expertise in the field of Artificial Intelligence, Machine Learning and IoT, he has a proven work record of delivering more than 100+ workshops and Technical Training in various technologies and domains at the top MNCs, premier organizations including IITs, NITs and other premier educational organizations. He has delivered 50+ corporate Training to clients from India and abroad. Skills- Programming Languages: Python, Arduino, R, MATLAB Scripting Languages: HTML, JS, CSS AI Skills: Machine Learning – Linear & Logistic Regression, Clustering, Artificial Neural Networks, SVM, Genetic Algorithm, Fuzzy Logic, Natural Language Processing, PCA, CNN, LSTM AI, ML Tools & Platforms: Python, Tensorflow, Keras, Azure ML, AWS, Apache Spark Hardware: Arduino, Raspberry Pi, AVR, Intel Edison, Xbee, LoRaWAN IoT Platforms: AWS IoT, Thingworx, ThingsBoard, IBM Watson IoT, ThingSpeak, myDevices, Twilio, node-red, Ubidots, PubNub, IoT Gateway


11 ratings
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  • April 23, 2020 at 12:19 pm

    I thoroughly enjoyed this course and hope to expand on my gained knowledge about data science. The course was well presented, easy to follow and engaging. The interactive examples make the course material easier to grasp. I definitely recommend this course to anyone who wishes to learn about data science.

  • April 23, 2020 at 12:00 pm

    I have learned a lot from the course and I am absolutely sure that I can apply everything I have learned in the course to solve product usability problems.This the second course I have taken from TechTrunk and I feel that I am achieving a good understanding of data science with R & Python

  • April 23, 2020 at 11:25 am

    I received my certificate, and I would like to thank you for your support. Your course was challenging, but you were always there supporting me and ready to help. I enjoyed this course tremendously. I look forward to taking another course with you.

  • April 1, 2020 at 08:38 am

    I have completed course very well, LMS and Projects work are the best part of training and the way of teaching is awesome. Thanks

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