Data Science

Here are some prerequisites to get familiar with Data Science.
  1. Knowledge of at least one programming language (Python, R, Matlab, etc)
  2. Concepts of Statistics (Descriptive and Inferential statistics)
  3. Data analysis
  4. Different Mining Techniques (Clustering, Classification, etc)
  5. Machine Learning
  6. Deep Learning
Want to become an expert in Data Science? Follow the below steps.
  1. Get familiar with basic Data Structures in python
  2. Learn about different libraries and packages (Numpy, Pandas, Matplotlib, Seaborn, Scikit, etc)
  3. Understand Descriptive and Inferential statistics
  4. Learn to understand and analyze a dataset
  5. Learn different Machine Learning techniques through python
  6. Learn different Deep Learning techniques through python







Web Development

Eager to learn Web Technologies?
Below are some topics to dive deep into Web Development.







Android App Development

Interested in App Development? With the increasing usage of the smartphone, there is a huge demand for Android / IOS /Crossed platform App developers.
Follow the below steps to become an expert in Android App Development.
  1. Basic Idea of Android studio 3.Different Media accessing (Photos, videos, audios, etc)
  2. Basic Java Programming
  3. Different Media accessing (Photos/videos/audios..etc)
  4. Advanced Android features
  5. Different Storages and integration with databases
  6. Crossed Platforms







Data Warehouse

Not much interested in programming? But want to work with the data? Why not try Data Warehousing? Here are some topics to get familiar with data warehousing.
  1. Introduction to Data warehouse
  2. Introduction to Business Intelligence
Some of the most commonly used BI Tools


  1. Data warehouse and Architecture
  2. Operational data store (ODS) / DWH/ OLTP/OLAP
  3. Data Mart
  4. Data Modelling Techniques
  5. Entity Relation Data (ERD) Model

Extract Transfer and Load (ETL). Below are the most commonly used ETL Tools used in industries.









Block Chain

Blockchain Technology is one of the emerging technologies. Which has wide scope and demand in the market. To be familiar with Blockchain you need to follow steps. Before going forward Blockchain is purely technical and one should have coding skills. As a prerequisite you must be familiar with java, JavaScript, NodeJS language. You should have an idea on the containerizing platform like (PaaS).
Introduction to Blockchain
    1. Transactions 
    2. Types of Network
    3. Distributed Network
    4. Ledgers
Blocks
Blockchain
    5. Introduction of Cryptocurrency Basics of Cryptography 
    6. Different cryptographic techniques 
        a. Hashing
        b. Digital Signatures 
        c. Public and Private key in transactions 
    7. Consensus and Different Consensus protocols
Proof of work (PoW)
Proof of stake (PoS)
Proof of capacity
Proof of Elapsed Time
Practical Byzantine Fault Tolerance (PBFT)
Blockchain Mechanism 
Structure of Blockchain
Basic Terminologies:
		Block 
		Hash
		Smart contracts
		Genesis Block
		Consensus algorithms
		Double spending
		Mining				
		Different Actors in Blockchain: 
			Blockchain developer
			Blockchain operator
			Blockchain regulator
			Blockchain user
Different cryptocurrencies:
Ethereum:
	 Terminologies:
			EVM
			Gas
			Smart contracts
			Transaction fee 
			Ether
	Smart Contracts implementation
	Solidity Language
	Redmix compiler
	Developing Environments 
			Truffle
	Decentralized applications
	Decentralized Autonomous organization (DAO)
	Blockchain Frameworks
	Importance of hyperledger
	Chaincode and it’s impotrance
	Implementation of chaincode
Hyperledger Fabric
Fabric model







Big Data

If you are new to bigdata. It’s always suggested to start from the basics.
Hadoop Ecosystem

High Performance Engines



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