ArtificialIntelligenceFoundationAn Industry recommended andvalidated course aligned toSSC NASSCOM Artificial IntelligenceFoundation curriculum

Duration: 58+ HoursPrice: ` 9,971/- (Inclusive of Taxes)

Learn IT

Self Paced Course

Overview

Assignment• Number of Auto Graded Assessments- 10 MCQ type• Number of Auto Graded Coding Problems on Virtual Lab- 28• One Final Assessment for Certification

TotalCurriculumDuration:

58+Hours

No. ofVideos - 45VideoDuration:

34+Hours

C C++ Java Python TableauR SQL

Tools

Assignment Duration: Student Effort:

24hours

70hours

Description

AI present opportunities to complement and supplement human intelligence and enrich the way people live and work. India, being the fastest growing economy with the second largest population in the world, has a significant stake in the AI revolution. This creates a need to enhance and empower young Indians with the skills to scale Indian-made AI solutions that can be implemented to the developing world.

Pearson’s Artificial Intelligence Foundation curriculum is created and taught by globally renowned experts in the field of AI ensuring world class content. The self-paced videos are complemented by virtual labs which provide extensive hands-on coding practice within the course environment. Regular auto graded MCQ type quizzes are embedded within the course for self-assessment and a final assessment in the end.

Highlights

Leading Instructors: Learn from internationally renowned AI experts Technology

in Action: Concepts are demonstrated with plenty of real-life use cases

Learn Anytime, anywhere: Learn at your pace on any device for minimum disruption to your job and family life

Flaunt Your Skills: Receive a certificate from Pearson, the world's leader in professional learning, and showcase your skills

Learning Outcomes

• Evaluate the technological trends which have led to AI

• Appreciate the potential of AI in transforming businesses

• Explain the various and diverse applications of data science

• Define common data science terminologies

• Evaluate the fundamentals of databases, Object-Oriented Programming and data structures

• Write programs in R

• Evaluate the fundamentals of statistics

• Perform basic analytical techniques such as regressions

• Evaluate the fundamentals of different forms of graphs

• Evaluate the characteristics and uses of various popular tools used for data science and visualizations

Who should take this course:

• University students enrolled in streams such as Engineering, Computer Science, Statistics, Sciences or Mathematics

• Employed professionals who wish to explore their career options and interests with regards to AI

• Enthusiasts curious about understanding the hype behind AI

Course Requirements:

Understanding of the fundamentals of programming, including arrays, matrices, functions, sorting, searching, pointers and knowledge of basic programming concepts such as object-oriented programming, classes and methods, polymorphism, inheritance and standard libraries

Downloads Required

A free version of Tableau Public software has to be downloaded by the learner in the last module of the course. Download link will be provided and the learner will be able to download by filling up his/her email in the required field. The learner should also create a free account on tableau with his/her email and they can use the software for as long as they want without any restriction.

Curriculum Fee

INR 8450 + Applicable Taxes= INR 9971

Curriculum

Module 1:Overview of AI

Module 2:Relational Data Bases

Module 3: Principles ofMachine Learning

Module 4: Foundationsand Implementation ofData Structures

Module 5:Algorithms

Module 6:R Programming

Module 7: Basic statisticsand Fundamentals ofData Visualization

Module 8: Graph types,tools and Libraries

Topics Covered-• Evolution of AI• Difference between narrow, general and super AI• Applications of AI across industries• Opportunities in AI for individuals, organizations and the ecosystem

Topics Covered-• Structure of Important algorithms

• Sorting and Searching Algorithms

Topics Covered-• Evolution and Applications of R• Basic data types in R• Expressions and Variables in R• Conditional statements, Loops and Iterations, Functions and Debugging in R

Topics Covered-• Pie charts• Line graphs• Scatter graphs• Bar charts• Column graphs• Ring plots• Ggplot• Bokeh• Tableau

Topics Covered-• Basic concepts of descriptive statistics• Measures of central tendency (mean, median, mode)• Measures of central dispersion (range, interquartile range, variance, standard deviation) and Regression• Simple data visualizations• Graph types• Statistical anomalies• Popular Dashboards• Characteristics of easy-to-consume visualizations

Topics Covered-• Introduction to SQL databases• Basic syntax, selecting and retrieving and sorting data• Filtering and calculating data• Subqueries and joins• Modifying and analyzing data

Topics Covered-• Basics of Machine Learning• Fundamentals of Supervised Learning concepts• Fundamentals of Unsupervised Learning concepts

Topics Covered-• Abstract Data types and Standard Template Libraries• Map Abstract Data Types to STL of Different Programming Languages• Mathematical properties of sequences • Special types of sequences (stacks, queues, strings, list, trees)• Implementation of sequences• Creating Graphs using OOP Paradigm

Faculty Details

Noah GiftFounder Pragmatic AI Labs | Author |

Northwestern & Berkeley & UC Davis ML Lecturer | CTO | ML Engineering Expert

Ben FortaAdobe- Senior Director of Education

Initiatives | SQL Bestseller

Jared P. LanderFounder- Lander Analytics | Adjunct Professor - Columbia University | Author of R for Everyone | Organizer of the

World's Largest R Meetup

Contact us:ppp.edge@pearson.comhttps://in.pearson.com/ppp0124 – 4185100

Pearson Professional Programs,Vatika First Indian Place, Tower C,Ground Floor (Near M.G. RoadMetro Station), Gurugram, India