Academy of Data Science

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MicroDegree Program in Data Science
with Python

Course Duration

  • 180 Hours
  • 5 sessions/week

Tools Covered

  • Python & ML
  • MSSQL, ETL & SSIS
  • Power BI

Learning Mode

  • Online Live Classes
  • One on one Interactive session

We provide

  • Special sessions for doubt solving
  • Sessions recordings (on request)
  • Sessions documents (on request) 
  • Assignments Mock interview
  • Live Projects

Python Course Content

Introduction to Python

  1. What is Python?
  2. Why Python?

Variables in Python

  1. What is Variable?
  2. Variables and Constants in Python
  3. Variable, names and Value
  4. Values and Types
  5. What Does “Type” Mean?

String Handling

  1. What is string?
  2. String operations and indices
  3. Basic String Operations
  4. String Functions, Methods
  5. Delete a string
  6. String Multiplication and concatenation
  7. Python Keywords, Identifiers and Literals
  8. String Formatting Operator
  9. Structuring with indentation in Python
  10. Built-in String Methods
  11. Define Data Structure?
  12. Data Structures in PYTHON

Python Operators and Operands

  1. Arithmetic, Relational Operators and Comparison Operators
  2. Python Assignment Operators
  3. Short-hand Assignment Operators
  4. Logical Operators or Bitwise Operators

Python Conditional Statements

  1. How to use “if condition” in conditional structures
  2. if statement (One-Way Decisions)
  3. if .. else statement (Two-way Decisions) 
  4. How to use “else condition”
  5. Logical Operators or Bitwise Operators
  6. if .. elif .. else statement (Multi-way)
  7. How to use “elif” condition
    Nested IF Statement

Python LOOPS

  1. How to use “While Loop” and “For Loop”
  2. How to use For Loop for set of other things besides numbers
  3. Break statements, Continue statements, Enumerate
  4. function for For Loop
  5. Practical Example
  6. How to use for loop to repeat the same statement over and again
  7. Break, continue statements

Learning Python Strings

  1. Strings
  2. Lists
  3. Tuples

Python Lists

  1. Lists are mutable
  2. Getting to Lists
  3. List indices
  4. Traversing a list
  5. List operations, slices and methods
  6. Map, filter and reduce
  7. Deleting elements
  8. Lists and strings

Python TUPLE

  1. Advantages of Tuple over List
  2. Packing and Unpacking
  3. Comparing tuples
  4. Creating nested tuple
  5. Using tuples as keys in dictionaries
  6. Deleting Tuples
  7. Slicing of Tuple

Python Sets

  1. How to create a set?
  2. Iteration Over Sets
  3. Python Set Methods
  4. Python Set Operations
  5. Union of sets
  6. Built-in Functions with Set
  7. Python Frozenset

Variables in Python

  1. What is Variable?
  2. Variables and Constants in Python
  3. Variable, names and Value
  4. Values and Types
  5. What Does “Type” Mean?

Python Dictionary

  1. How to create a dictionary?
  2. Python Dictionary Methods
  3. Copying dictionary
  4. Updating Dictionary
  5. Delete Keys from the dictionary
  6. Dictionary items() Method
  7. Sorting the Dictionary
  8. Python Dictionary in-built Function
  9. Dictionary len() Method
  10. Variable Types
  11. Python List cmp() Method
  12. Dictionary Str(dict)

Python Functions

  1. What is a function?
  2. How to define and call a function in Python
  3.  Types of Functions
  4.  How Function Return Value?
  5. Types of Arguments in Functions
  6. Default Arguments and Non-Default
    Arguments
  7. Keyword Argument and Non-keyword
    Arguments
  8.  Rules to define a function in Python
  9. Scope and Lifetime of variables
  10.  Nested Functions
  11. Call By Value, Call by Reference
  12. Passing functions to function

Python Date and Time

  1. How to Use Date & DateTime Class
  2. How to Format Time Output
  3. How to use Timedelta Objects
  4. Calendar in Python
  5. datetime classes in Python
  6. How to Format Time Output?
  7. The Time Module
  8.  Python Calendar Module
  9. Python Text Calendar, HTML Calendar Class
  10. Unix Date and Time Commands

File Handling

  1. What is a data, Information File?
  2. File Objects
  3. File Different Modes and Object Attributes
  4. How to create a Text Fil and Append Data to a File and Read a File
  5. Closing a file
  6. Read, read line ,read lines, write, write
    lines…!!
  7. Renaming and Deleting Files
  8. Directories in Python
  9. Working with CSV files and CSV Module
  10. Handling IO Exceptions

Python Exception Handling

  1. Chain of importance Of Exception
  2. Exception Handling
  3. Try … Except
  4. Try .. Except .. else
  5. Try … finally
  6. Argument of an Exception
  7. Python Custom Exceptions
  8. Ignore Errors
  9. Assertions
  10. Using Assertions Effectively

More Advanced PYTHON

  1. Python Iterators, Generators, Closures,
    Decorators and Python @property

Python Class and Objects

  1. Introduction to OOPs Programming
  2. Object Oriented Programming System
  3. OOPS Principles
  4. Define Classes
  5. Creating Objects
  6. Class variables and Instance Variables
    Constructors
  7. Basic concept of Object and Classes

Machine Learning Course Content

1. Introduction to Machine Learning

  1. Machine Learning
  2. Machine Learning Algorithms
  3.  Algorithmic models of Learning
  4. Applications of Machine Learning
  5. Large Scale Machine Learning

2. Techniques of Machine Learning

  1. Supervised Learning
  2. Unsupervised Learning

3. Regression

  1. Regression and its Types
  2. Logistic Regression
  3. Linear Regression
  4. Polynomial Regression

4. Classification

  1. Meaning and Types of Classification
  2.  Nearest Neighbor Classifiers
  3. K-nearest Neighbors
  4. Probability and Bayes Theorem
  5. Support Vector Machines
  6. Naive Bayes
  7. Decision Tree Classifier
  8. Random Forest Classifier

5. Unsupervised Learning: Clustering

  1. About Clustering
  2. Clustering Algorithms
  3. K-means Clustering
  4.  Hierarchical Clustering
  5.  Distribution Clustering

6. Model optimization and Boosting

  1. Ensemble approach
  2. K-fold cross validation
  3. Grid search cross validation
  4. Ada boost and XG Boost

Power BI Course Content

1. Introduction to Power BI

  1. Overview of BI concepts
  2. Why we need BI?
  3. Introduction to SSBI
  4. SSBI Tools
  5. Why Power BI?
  6. What is Power BI?
  7. Building Blocks of Power BI
  8. Getting started with Power BI Desktop
  9. Get Power BI Tools
  10. Introduction to Tools and Terminology
  11. Dashboard in Minutes
  12. Refreshing Power BI Service Data
  13. Interacting with your Dashboards
  14. Sharing Dashboards and Reports

2. Power BI Desktop

  1. Power BI Desktop
  2. Power BI Dashboards
  3. Power BI Q & A
  4. Extracting data from various sources
  5. Workspaces in Power BI
  6. Data Transformation
  7. Measures and Calculated Columns
  8. Query Editor 

3. Modelling with Power BI

  1. Introduction to Modelling
  2. Modelling Data
  3. Manage Data Relationship
  4. Optimize Data Models
  5. Cardinality and Cross Filtering
  6. Default Summarization & Sort by
  7. Creating Calculated Columns
  8. Creating Measures & Quick Measures

4. Data Analysis Expressions (DAX)

  1. What is DAX?
  2. Data Types in DAX
  3. Calculation Types
  4. Syntax, Functions, Context Options
  5. DAX Functions
  6. Date and Time
  7. Time Intelligence
  8. Information
  9. Logical
  10. Mathematical
  11. Statistical
  12. Text and Aggregate
  13. Measures in DAX

5.Publishing and Sharing

  1. • Introduction and Sharing Options Overview
  2.  Publish from Power BI Desktop and Publish to
    Web
  3.  Share Dashboard with Power BI Service
  4. Workspaces and Apps (Power BI Pro) and
    Content Packs (Power BI Pro)
  5. Print or Save as PDF and Row Level Security
    (Power BI Pro)
  6. Export Data from a Visualization and Publishing
    for Mobile Apps
  7. Export to PowerPoint and Sharing Options
    Summary

6. Refreshing Datasets

  1. Understanding Data Refresh
  2. Personal Gateway (Power BI Pro and 64-bit
    Windows)
  3. Replacing a Dataset and Troubleshooting
    Refreshing

MS SQL Course Content

1. Databases – MySQL and SQL Queries

  1. Introduction to MySQL
  2. What is the MSSQL?
  3. How do I Install MSSQL?
  4. Connecting to the MSSQL
  5.  Creating and Selecting a database
  6.  Adding data to a table
  7. Executing multiple queries
  8. Exporting and Importing data tables.

2. Structural & Functional Database Management (DDL DML)

  1. SQL Syntax
  2. SQL Create Command
  3. SQL Alter Command
  4. SQL Truncate
  5. SQL Delete
  6. SQL Update
  7. SQL Set
  8. SQL Select
  9. SQL Distinct
  10. SQL Where Clause
  11. SQL And & Or
  12. SQL Order By
  13. SQL Insert 
  14.  

3. SQL Functions

  1. Single Row Functions
  2. String Functions, Aggregate Function, Round,
    Truncate, Max, Min, Date-Time Functions
  3. General Functions
  4. Count, Average, Sum etc.

4. Joining Tables

  1. Obtaining data from Multiple Tables
  2. Types of Joins (Inner Join, Left Join, Right Join &
    Full Join)
  3. Sub-Queries Vs. Joins

5. Operators (Data using Group Function)

  1. Distinct, Order by, Group by, Equal to etc. 

6. Database Objects (Constraints & Views)

  1. Not Null
  2. Unique
  3. Primary Key
  4. Foreign Key

7. SQL Advance

  1. SQL Like
  2. SQL Wildcards
  3. SQL In
  4. SQL Between
  5. SQL Alias
  6. SQL Union/Union All

8. SSIS SQL Server Data tool (SSDT)

  1. Data Import Export
  2. Transformations
  3. Variables
  4. Parameters
  5. Containers 

9. SQL Aggregate Functions

  1. SQL Avg()
  2. SQL Count()
  3. SQL Max()
  4. SQL Min()
  5. SQL Sum()
  6. SQL Group By clause
  7. SQL Having clause