Data structures

1. Data Structures
Duration: 1.5 Months
Fees: Rs 4500/-
A1/17, Top Floor, Opposite Metro Pillar no: 636, Main Najafgarh ,Road, Janakpuri New
Delhi – 110058
Phone no-011-4166-8088, 90155-96280, 9313565406, website-www.balujalabs.in

2. Data Structures
1. Introduction
• Definition
• Classification of Data Structures
• Description of Various Data Structures
• Arrays
• Lists
• Stack
• Queues
• Trees
• Graph
• C++ Memory Allocation in C++
• Memory Allocations in C++
• Free Store
• Memory Allocation Operators
• New
• Delete
• Memory Leaks
• Algorithms
• Performance Analysis & Measurement
• Space Complexity
• Time Complexity
• Big OH Notation
• Categories of Algorithms
• Limitation of OH Notation
2. Recursion- A Breath Breaker
• Introduction
• Types of Recursion
• Storage Classes
• Automatic Storage Class
• Register Storage Class
• Storage Class
• Static Storage Class
• Recursion Essentials
• Disadvantages of Recursion
• Simple Recursive Program
• Tower of Hanoi
• Recursion vs Iterations
• Arrays
• Introduction
• One-dimensional Arrays
• Initializing One-dimensional Array
• Accessing One- dimensional Array Elements
• Implementation of dimensional Array in Memory
• Passing Rays for Function
• Insertion in One-dimensional Array
• deleting an Element form One-dimensional Array
• Traversing of Arrays
• Merging Two Arrays
• Combining All Together
• Multi-dimensional Arrays
• Initialization of Multidimensional Arrays
• Accessing Two-dimensional Arrays

3. 4. Stacks
• Introduction
• Stack Implementation
• Operations on Stack
• Stack Terminology
• Algorithms for Push and Pop
• Implementing Stacks
• Applications of Stacks
• Stack Frames
• Reversing a String
• Calculation of Postfix Expression 4.7.3A Notation
Conversions
• Algorithm for Converting Infix Expression to
Postfix form
• Algorithm to Evaluate a Postfix Expression
5. Queues
• Introduction
• Queue Implementation
• Operations on a Queue
• Operations on a Queue
• Algorithms for Insertion and Deletion in Queue
• Algorithm for Addition in a Queue
• Algorithm for Deletion From a Queue
• Limitation of Simple Queues
• Algorithm for Insertion and Deletion in Queue
• Variations in Queue
6. Linked Lists
• Introduction
• Linked Lists
• Advantages
• Disadvantages
• Key Terms
• Representation of Linear Linked List
• Operation on Linked List
• Type of Linked List
• Singly Linked List
• Inserting Nodes
• A Inserting A Node at the Beginning
• B Inserting A Node at the end
• C Inserting A New Node at the specific position

4. Data Visualization
• Part -3 Data Visualization: MODULE 1
• Line Plots
• Bar Plots
• Pie Plots
• Scatter plots
• Histogram Plots
• Saving plots to file
• Plotting functions in matplotlib
• Matplotlib
MODULE 2 Seaborn
• I ntroduction of Seaborn
• Distribution Plots
• Categorical Plots
• Matrix Plots
• Bar Plots
• Box Plots
• Strip Plots
• Violin Plots
• Clustermap Plots
• Heatmaps Plots
• KDE Plots
• Regression Plots
• 12. Style and Color
• 14. Seaborn Exercise
MODULE 3 Plotly and Cufflinks
• Introduction to Plotly and Cufflinks
• Plotly and Cufflinks
MODULE 4 Geographical Plotting
• Introduction to Geographical Plotting
• Choropleth Maps – Part 1
• Choropleth Maps – Part 2
• Choropleth Exercises
• Projects using Analysis and Visualisation
Machine Learning
Part -4 Machine Learning: MODULE 1 Introduction
to Machine Learning
• What is Machine learing?
• Overview about scikit-learn package
• Types of ML
• Basic steps of ML
• ML algorithms
• Machine learning examples
MODULE 2 Data Preprocessing
• Dealing with missing data
• Identifying missing values
• Handling with categorical data
• Imputing missing values
• Nominal and Ordinal features
MODULE 3 Machine Learning Classifiers
• K-Nearest Neighbors (KNN)
• Decision tree
• Random forest
• Naive Bayes
• Logistic Regression

5. State management
• State Management with HTTP
• Page Server
• View State
• User level
• Session
• Application Level
• Application
• Website
• Cookies
• Cleaning the session State
• Global Application class (global. asax)
• Web configuration file ( web.config)
• Web Caching
Intrinsic objects under Asp.Net
• Request Object
• Response Object
• Session Object
• Application Object
• Server Object
• View State object
Advanced Asp.Net
• Using FTP software
• Using Browser
• Creting Web Setup Project
• Component Programming(Data Logic Layer)
• Ajax
LINQ
• C# Language Extensions in 3.5 (Prerequisite)
• ?Type Inference
• ?Object Initializers.
• ?Anonymous Types
• Extension Methods
• ?Partial Methods
LINQ Architecture
• Understanding the LINQ Framework
• LINQ Providers
• LINQ to Objects
• LINQ to SQL
• LINQ to Dataset
• LINQ to XML
LINQ to Objects
• ?IEnumerable<T> and IQueryable<T> interfaces
• System.Linq namespace
• Query Expressions
• Lambda Expression
• Using Custom Class Collection
LINQ to SQL
• Defining the Data Model classes
• ?Using Mapping attributes
• Using the Data Context class
• Defining Relationships using Associations
• Creating a customized Data Context class

6. MODULE 4 Regression Based Learning
• Simple Regression
• Multiple Regression
• Predicting house prices with Regression
MODULE 5 Clustering Based Learning
• Definition
• Types of clustering
• The k-means clustering algorithm
MODULE 6 Natural Language Processing
• Install nltk
• Tokenize words
• Tokenizing sentences
• Stop words with NLTK
• Stemming words with NLTK
• Twitter Sentiment analysis Project
MODULE 7 Working with OpenCV
• Installing opencv
• Reading and writing images
• Applying image filters
• Writing text on images
• Image Manipulations
• Face detection Project
• Speech Recognition Project
Python with Data Science
1. Python with Data Science
• Baric of Python Spider (Tool)
• Introduction Spider
• Setting Working Directory
• Creating and Saving a Script file.
• File Execution
• Clearing Environment
• Commentary Script File
• variable creation
• Arithmetic & Logical operator
• Data type & associates operations
2. Data Structures
• List
• Tyler
• Dictionary
• Sets
3. Numpy
• Array
• Matrix and associated operation
• Linear algebra & related operations
4. Panda data frame and data framerelated operations on
Toyoter Corolla data sets
• Reading File
• Exploratory data Analysis
• Data preparation and processing
5. Data visualization on Toyo to Corolla
dataset using matplotlib and seaborne libraries
• Scalther plot
• Line plot
• Bar plot
• Historiography
• Box plot
• Pain plot

7. 6. Control Structure using Toyota Corolla data
sets
• If else family
• for loop
• for loop with if break
• While loop
• Functions
• CASE STUDY
• Regression
• predicting price of powered cares
Clarification
• Clarification personal income

8. A1/17, Top Floor, Opposite Metro Pillar no: 636, Main Najafgarh
Road, Janakpuri New Delhi – 110058
011-4166-8088, 90155-96280, 9313565406
www.balujalabs.in
Course Highlight
1.Consistent Classroom Guidance
2.Meticulously designed Study Material
3.Review of Previous years question papers
4.Regular model Mock tests on exam patterns
5.One on One attention
6.Time Bound Completion
7. Experienced full time faculty
8.Small batches
9.5 days a weekend batches
10.Weekly test
11.Accommodation for outstation students(PG)