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DATA STRUCTURES AND ALGORITHMS
Home
DSA
Data Science and BDA
1. Intro to DS and BD
Basics and Need
Application of DS
Data Explosion
5 V's of Bigdata
Relationship DS IS
BI VS DS
DS Life Cycle
Data Types collection
Need of Wrangling
Methods
2. Statistical Inference
Need of Statastics
Measures of CT
Measures of Dispersion
Bayes Theorem
Need of Hypothesis
Pearson Correlation
Sample Hypothesis testing
Chi-Square Tests
t-test.
3. BD Analytics L_Cycle
Sources of BD
Data Analytic Lifecycle
Phase1 Discovery
Phase2 Data Preparation,
Phase3 Model Planning
Phase4 Model Building
Phase5 Comm results
Phase6 Operationalize
4. Predictive BDA with Py
Essential Libraries
Data Preprocessing
Analytics Types
Association Rules
Linear Regression
Logistic Regression
Naïve Bayes
Decision Trees
Intro Scikit-learn
5. BDA and Model Eval
K-Means
Hierarchical Clustering
Time-series analysis
Text Analysis
Model Evaluation
Model Selection
6. Data Visual and Hadoop
Introduction
Challenges
Types
Techniques
Visualizing Big Data
Tools used
Hadoop ecosystem
Map Reduce
Pig, Hive
Analytical techniques
All plot
Python
1.PPS
Problem Solving
Decision Control stmnt
2.FPP
Python Basics
Introd to PL
What is Python
Python Install
Python keywords
List Dict Set Tuple
Copy Operation
Decision Control stmnt
Blockchain
1. Mathem_Founda
Symmetric Key
UGC NET Question
Asymmetric Key
Elliptic_Curve_Basics
EC_Cryptography
Crypt_Hash Function
Need DDC
SHA 256 Algorithm
Digi_Sign_Algorithm
Merkel Tree
2. Feature Engineering
History BT
Appl_and_Exec_Layer
Sem_and_Propa_Layer
Consensus Layer
Why BT Important
Limitation of CS
3. Blockchain_Platforms
Types of Platforms
Pub_Pri_nd_Consortium
Bitcoin_Ethereum_Hype
IoTA_CORDA_R3
Consensus Approach
Consensus Elements
Consensus Algorithms
Proof of Work
Byzantine General Problem
Proof of Stake
Proof of Elapsed Time
Proof of Activity
Proof of Burn
4.Cryptocurrency
Introduction
Cryptowallets:MM_CB_Bin
5.Blockchain_Ethereum
What is Ethereum
SC_using_Solidity
Swarm(Decen_Sto_Plat)
Whisper (Decen_Mesg_Plat)
6. Blockchain_Case_Studies
Prominent_BT_APP
Retail BankingFS
Govt_Sect_Healthcare
IOT Ene_nd_Utili
BT Int_with_other_Domain
Deep Learning
Syllabus
1. Foundations of DL
Machine Learning
Introduction to DL
Working of DL
Application of DL
2. Deep Neural Networks
Intro to Neural n/w
Activation Function
Loss Function
HyperParameters
3. Laboratory Practice V
1.House Price
2. Classification
CNN Problem
Mini Project
Python
1.PPS
Problem Solving
Decision Control stmnt
2.FPP
Python Basics
Introd to PL
What is Python
Python Install
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List Dict Set Tuple
Copy Operation
Decision Control stmnt
Web Technology
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Exception Handling
Managing I/O
2.Unit 5(SPPU)
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