Page 13 - Ai_V3.0_c11_flipbook
P. 13

Students will be able to:             Machine Learning in a nutshell    Calculation  of  of  pearson
                                                                                                correlation coefficient in MS –
                    MACHINE LEARNING ALGORITHMS    Apply  these methods to develop     Understanding  Correlation,    Demonstration of k  – Nearest
                              Differentiate  the  different  types  of
                                                                 Types of Machine Learning
                                                                                                Excel.
                             machine learning methods.
                                                                 Supervised Learning
                                                                                                                   Linear
                                                                                                Demonstration
                              They will be able to  understand
                                                                                                regression  in MS – Excel  /
                             the  concept  behind  each  machine
                                                                 Regression,  Finding the line,
                                                                                                using python program.
                             learning methods.
                                                                 Linear Regression algorithm
                                                                 Classification  –  How  it  works,
                                                                                                Neighbour
                                                                                                                  python
                                                                                                           using
                             simple solutions for some day-to- day
                                                                 Types,  k –  Nearest Neighbour
                                                                                                program.
                             situations.
                                                                 algorithm
                                                                                                Demonstration of k  –  means
                              Build up this  knowledge  to the  next
                                                                 Unsupervised Learning
                                                                                                clustering
                                                                                                           using
                             level to apply during Capstone Project
                                                                                                program.
                                                                 Clustering – How it works, Types,
                             development.
                                                                 k -means Clustering algorithm

                                                                                                IBM SkillsBuild - Machine
                                                                                                learning with Python  python
                           Students will be able to:             Understanding  to  Natural     Write an article on “IBM Project
                                                                                    Human
                                                                                                Debater – Interesting facts”
                                                                 Language Complexity
                              Develop  a  better  understanding  of
                    LEVERAGING LINGUISTICS AND   COMPUTER SCIENCE    Learn new techniques and algorithms     Phases of NLP and  Sentiment           following platforms:
                                                                                                Create a  chatbot on ordering
                             the complexities of language and the
                                                                 Introduction
                                                                 Language Processing  (NLP) -
                                                                                                ice-creams using  any of  the
                             challenges involved in NLP tasks.
                                                                 Emotion
                             for NLP tasks.
                                                                 Detection
                                                                                                      Google Dialogflow
                                                                                                o
                                                                 Analysis, Classification Problems,
                                                                                                o
                                                                                                      Botsify.com
                                                                 Chatbot
                                                                                                o
                                                                                                      Botpress.com
                                                                                                IBM SKillsBuild - Natural
                                                                 Applications of NLP
                                                                                                Language Processing
                           Students will be able to:             Ethics in Artificial Intelligence    Summarize your insights and
                              Demonstrate an understanding of the     The five pillars of AI Ethics  interpretations from the video
                             fundamental principles of ethics and     Bias, Bias Awareness, Sources of   "Humans need not apply.”
                             gain insight into ethical considerations   Bias                    Activity: Role Play on biased AI
                             related to AI technologies.         Mitigating Bias in AI Systems     systems
                    AI ETHICS AND VALUES    Identify and apply strategies for     Moral Machine Game    Comparative  guidelines involve
                              Develop an understanding of AI
                                                                                                IBM SkillsBuild - AI Ethics
                                                                 Developing AI Policies
                             bias, its sources, and its real-world
                                                                                                                      of
                                                                                                              study
                             implications, as well as the ethical
                                                                                                    policies
                                                                                                            (that
                                                                                                AI
                             considerations.
                                                                                                examining
                                                                                                                    and
                                                                 Survival of the Best Fit Game
                                                                                                                     by
                                                                                                          established
                                                                                                principles)
                             mitigating bias in AI systems to
                                                                                                                    and
                                                                                                        organizations
                                                                                                various
                                                                                                regulatory bodies
                             promote fairness and transparency in
                             technology.
                              Recognize the significance of AI                                  Understanding     ethical
                                                                                                dilemma using
                             policies  in  promoting  responsible,                              Moral machine  Survival of the
                             safe, and ethical use of AI technologies.                          best fit
                                                               PART – C
                 1.   Practical File
                 Note: The following to be included in Practical File
                      •  one certification (IBM Skills Build /any other industry certification)
                      •  at least one activity from each unit
                      •  one participation certificate of bootcamp/internship
   8   9   10   11   12   13   14   15   16   17   18