Artificial Intelligence Course

Artificial Intelligence course is offered by MS Soft Technologies. MS Soft Technologies is a leading software training institute dedicated to providing high-quality education with real-time industry experts. We offer a wide range of professional courses.

Artificial Intelligence Course Syllabus:

• Introduction to Deep Learning & AI
• Deep Learning: A revolution in Artificial Intelligence
• What is Deep Learning?
• Need for Data Scientists
• Foundation of Data Science
• What is Business Intelligence
• What is Data Analysis
• What is Data Mining
• What is Machine Learning?
• Analytics vs Data Science
• Value Chain
• Types of Analytics
• Lifecycle Probability
• Analytics Project Lifecycle
• Advantage of Deep Learning over Machine learning
• Reasons for Deep Learning
• Real-Life use cases of Deep Learning
• Review of Machine Learning
•  Data
• Basis of Data Categorization
• Types of Data
• Data Collection Types
• Forms of Data & Sources
• Data Quality & Changes
• Data Quality Issues
• Data Quality Story
• What is Data Architecture
• Components of Data Architecture
• OLTP vs OLAP
• How is Data Stored?
• Big Data
• What is Big Data?
• 5 Vs of Big Data
• Big Data Architecture
• Big Data Technologies
• Big Data Challenge
• Big Data Requirements
• Big Data Distributed Computing & Complexity
• Hadoop
• Map Reduce Framework
• Hadoop Ecosystem
• Data Science Deep Dive
• What Data Science is
• Why Data Scientists are in demand
• What is a Data Product
• The growing need for Data Science
• Large Scale Analysis Cost vs Storage
• Data Science Skills
• Data Science Use Cases
• Data Science Project Life Cycle & Stages
• Data Acuqisition
• Where to source data
• Techniques
• Evaluating input data
• Data formats
• Data Quantity
• Data Quality
• Resolution Techniques
• Data Transformation
• File format Conversions
• Annonymization
• Python
• Python Overview
• About Interpreted Languages
• Advantages/Disadvantages of Python pydoc.
• Starting Python
• Interpreter PATH
• Using the Interpreter
• Running a Python Script
• Using Variables
• Keywords
• Built-in Functions
• StringsDifferent Literals
• Math Operators and Expressions
• Writing to the Screen
• String Formatting
• Command Line Parameters and Flow Control.
• Lists
• Tuples
• Indexing and Slicing
• Iterating through a Sequence
• Functions for all Sequences
• Operators and Keywords for Sequences
• The xrange() function
• List Comprehensions
• Generator Expressions
• Dictionaries and Sets.
• Numpy & Pandas
• Learning NumPy
• Introduction to Pandas
• Creating Data Frames
• GroupingSorting
• Plotting Data
• Creating Functions
• Slicing/Dicing Operations.
• Deep Dive – Functions & Classes & Oops
• Functions
• Function Parameters
• Global Variables
• Variable Scope and Returning Values. Sorting
• Alternate Keys
• Lambda Functions
• Sorting Collections of Collections
• Classes & OOPs
• Statistics
• What is Statistics
• Descriptive Statistics
• Central Tendency Measures
• The Story of Average
• Dispersion Measures
• Data Distributions
• Central Limit Theorem
• What is Sampling
• Why Sampling
• Sampling Methods
• Inferential Statistics
• What is Hypothesis testing
• Confidence Level
• Degrees of freedom
• what is pValue
• Chi-Square test
• What is ANOVA
• Correlation vs Regression
• Uses of Correlation & Regression
• and more