DATA SCIENCE

DATA SCIENCE

“Data Science” is an Inter-Disciplinary subject involving Mathematics, Statistics, Business acumen, Python, Machine Learning and Deep Learning etc., Using “Data Science”, we can analyse information which is collected or gathered from various sources of information and give an accurate solution to the problem in hand. With the help of Data Science, useful insights can be attained, related to the problems of Business, Society, Science and Technologies etc. Data Science helps Business Organisations or Companies to develop Business Strategies, leverage their Resource utilization, take accurate business decisions etc., Business Organisations can rein in their Cost of Production, increase Efficiencies, identity new Market Opportunities for their Products and achieve Competitive Advantage over their Competitors.

Eligibility for a course typically depends on the following:

  1. Prerequisites: Required prior courses or skills.
  2. Level of Study: Undergraduate, graduate, or continuing education.
  3. Program Requirements: Specific to your major or program.
  4. Open Enrollment: Available to all students as an elective.
  5. Special Permissions: Might need instructor or department approval.
  6. Availability: Limited seats may give priority to certain students.
  7. Location/Delivery: Online or specific campus availability.

Check the course catalog or consult with an academic advisor for specifics.

DATA SCIENCE – Course Content

Introduction
• What is Data Science?
• What are the key skills required to pursue Data Science?
• Why Data is the new oil and AI is the new electricity?
• How Data Science is changing the real-world applications at exponential rate ?
• Where Data Science can make miracles and change the face off the industry ?
• When to declare yourself as a Data Scientist ? or a Data Analyst ?
• Real world applications – Hands on experience
• Deployment of end to end Data Science project
Computation with Excel
Excel Introduction
Excel Get Started
Excel Overview
Excel Syntax
Excel Ranges
Excel Fill
Excel Move Cells
Excel Add Cells
Excel Delete Cells
Excel Undo Redo
Excel Formulas
Excel Relative Reference
Excel Absolute Reference
Excel Arithmetic Operators
Excel Parentheses
Excel Functions

Excel Formatting
Excel Format Painter
Excel Format Colors
Excel Format Fonts
Excel Format Borders
Excel Format Numbers
Excel Format Grids
Excel Format Settings

Excel Data Analysis
Excel Sort
Excel Filter
Excel Tables
Excel Conditional Format
Excel Highlight Cell Rules
Excel Top Bottom Rules
Excel Data Bars
Excel Color Scales
Excel Icon Sets
Excel Manage Rules (CF)
Excel Charts

Table Pivot
Table Pivot Intro

Excel Functions
AND
AVERAGE
AVERAGEIF
AVERAGEIFS
CONCAT
COUNT
COUNTA
COUNTBLANK
COUNTIF
COUNTIFS
IF
IFS
LEFT
LOWER
MAX
MEDIAN
MIN
MODE
NPV
OR
RAND
RIGHT
STDEV.P
STDEV.S
SUM
SUMIF
SUMIFS
TRIM
VLOOKUP
XOR

Excel How To
Create an Income Statement
Create a Task to-do list
Create a Balance Sheet

Real world Projects
Introduction to Excel
Learn Data Calculations
Learn Data Visualization
Learn to Create a Budget
Learn to Create a Timeline
Learn to Style in Excel

Excel Online Learning Resources
Excel Keyboard Shortcuts

Programming Essentials with Python
Python Intro
Python Get Started
Python Syntax
Python Comments
Python Variables
Python Data Types
Python Numbers
Python Casting
Python Strings
Python Booleans
Python Operators
Python Lists
Python Tuples
Python Sets
Python Dictionaries
Python If…Else
Python While Loops
Python For Loops
Python Functions
Python Lambda
Python Arrays
Python Classes/Objects
Python Inheritance
Python Iterators
Python Polymorphism
Python Scope
Python Modules
Python Dates
Python Math
Python JSON
Python Rage
Python PIP
Python Try…Except
Python User Input
Python String Formatting

File Handling
Python File Handling
Python Read Files
Python Write/Create Files
Python Delete Files
Python Modules
NumPy Tutorial
Pandas Tutorial
SciPy Tutorial
Django Tutorial
 
Statistics & Probability
Stat Introduction
Stat Gathering Data
Stat Describing Data
Stat Making Conclusions
Stat Prediction & Explanation
Stat Populations & Samples
Stat Parameters & Statistics
Stat Study Types
Stat Sample Types
Stat Data Types
Stat Measurement Levels
 
Descriptive Statistics
Stat Descriptive Statistics
Stat Frequency Tables
Stat Histograms
Stat Bar Graphs
Stat Pie Charts
Stat Box Plots
Stat Average
Stat Mean
Stat Median
Stat Mode
Stat Variation
Stat Range
Stat Quartiles and Percentiles
Stat Interquartile Range
Stat Standard Deviation
 
Inferential Statistics
Stat Statistical Inference
Stat Normal Distribution
Stat Standard Normal Distribution
Stat Students T-Distribution
Stat Estimation
Stat Population Proportion Estimation
Stat Population Mean Estimation
Stat Hypothesis Testing
Stat Hypothesis Testing Proportion
Stat Hypothesis Testing Mean
 
Probability 
Basic Probability
Probability Calculus
Bayes Theorem
Conditional Probability
Probability Distribution Functions and their types
 
Machine Learning Essentials
How Machine actually learns?
Importing Data from different files
Why ethics matter
Installation Guide
 
Algorithm List
Decision Trees
K-means Clustering
Principal Component Analysis
Market Basket Analysis
Correlation & Regression
K-Nearest Neighbors & Anomaly Detection
Support Vector Machine
Random Forest
Neural Network
Confusion Matrix
 
6-step Process
Step 1: Data collection
Step 2: Data exploration
Step 3: Data preparation
Step 4: Model instruction
Step 5: Model evaluation
Step 6: Model improvisation
 
Power BI Essentials
– Introduction
– Get Started
– Business Intelligence and Power BI
– Power BI products
– The Business Intelligence Employee Retention Dataset
– Install Power BI Desktop
– Launch Power BI Desktop
– Get Data
– Model data
– Fixing Headers
– Creating relationships
– Formatting Data
– Creating Calculated Columns
– Creating Measures
– Visualisations and Reports
– Column and Bar Charts
– Line and Area Chart
– Combo Charts
– Treemap, Gauge, Pie and Donut charts
– Maps
– Cards and tables
– Shapes and Images
– Custom Visuals
– Sales Dashboard
– Bookmarks
– Share Your Work
– Publishing in Power BI service
– Share and Publish to Web
– Real world Projects 
 
 

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