Learn to code for FREE

Sunday, 24 March 2019


Hello everyone! Do you want start your career in computer science, want to become a freelancer or want to become an entrepreneur and don’t have any skills? Then you are in right place for guidance.  I will tell about 10 best websites from where you can learn coding from scratch they would be absolutely free. If you’re brand new to the world of web design and web development, it makes sense that you should learn to code by using free resources available online. That way, you can discover what you like—and more importantly don’t—before committing to more in-depth courses. Even if you know you’re ready to learn coding, when you’re just getting started, it’s easy to become overwhelmed by all the free resources and coding classes out there.

To make things easier, I’ve compiled a list of 10 FREE web design and development resources for learning tech basics and mastering specific topics.

Pick and choose the ones that best suit your career goals, and you’ll learn how to code in no time. Enjoy!
  1.  Codecademy
  2.  Codewars
  3.  Coursera
  4.  edX
  5.  Free Code Camp
  6.  Khan Academy 
  7. MIT OpenCourseware
  8.  Udacity
  9.  Udemy 
  10. thenewboston


How to Become a Blockchain Developer

Tuesday, 15 May 2018


Blockchain, Crypto-Currencies, Ethereum, Smart Contracts and ICOs have become the most frequently used words in computer science, FinTech and investment circles these days. Everyone likes to have skin in the game — to invest, earn/lose, re-invest and become a millionaire before anyone else would know it.

Blockchain is doing to startups & businesses (in general) and FinTech (in particular) what Email has done to Post-office mails, Mobile Phones to Landlines, Netflix to Blockbusters, Amazon to RadioShack, and what Digital pictures have done to Kodak.
It’s the era of blockchain and distributed ledger technology — it’s not the question if and when you will realize it, it is how much you lose while taking the time to come to that realization.

William Mougayar mentioned in his book Business of Blockchain there are 5,000 blockchain developers in the world (Mid-2016); compare this with 9 million Java developers and 18.5 million software developers worldwide. According to the CEO of Pantera Capital, cryptocurrencies will hit the $40 trillion market cap. ComputerWorld says the median salary of a blockchain developer is $158,000/year and the hourly rate is $150/hour. UpWork has seen 3500% increase in blockchain skills demand over the year and according to TechCrunch there is only one candidate available for 14 blockchain jobs today. There is a job for every aspect of the blockchain ecosystem, there is a job if you know how to code smart contracts, there is a job for cryptography experts, there is a job for consensus developers, there is a job for Ripple suit of applications, and there is a job for IBM’s Hyperledger Fabric. It doesn’t matter which part of this ecosystem you work in, there is a job available (right now) for you. Portals like Blocktribe are dedicated to blockchain related jobs only. There are 5,000+ blockchain startups, and ICOs have raised close to $7 billion worldwide. The world would need half a million blockchain developers in next five years.

The question is what YOU can do to secure a job and make your dreams come true, and how YOU can become someone that would qualify for these half a million jobs worldwide.

Here is my cheat sheet of becoming a good Blockchain Developer for (almost) Free:

1. Start by watching Neha Narula’s Ted talk on the Future of Money
2. Don Tapscott’s talk on how blockchain is changing money and business should be your next click
3. Let’s take a step back to find out why we have stopped trusting institutionsby Rachel Botsman and the role of middlemen by BCG
4. Have a look at future of Branded Money with Paul Kemp
5. Mark Schwartz sheds light on Potential of Blockchain
6. We will end our visual journey with Bettina Warburg’s talk on Radical Transformation by Blockchain
7. As soon as you done watching these talks, read this article from HBR to gear up for the next phase
8. Make sure to bookmark these organizations for regular updates and to find out where the industry is heading — Digital Currency Initiative at MITOxford Blockchain NetworkDigital Chamber of CommerceR3HyperledgerConSenSysBlockchain Research Institute
9. Books: Here are a couple of good books to get started and all of these are available for FREE to download: Blockchain for DummiesMastering Blockchain 1st EditionA Gentle Introduction to Blockchain TechnologyMastering Bitcoin by Andreas M. Antonopoulos, Virtual Currency: the Bitcoin Manual by Lachlan Roy, A great book on how to become a blockchain developer by x-teamHandbook of Digital Currency — Bitcoin, Innovation, Financial Instruments and Big Data , Understanding Bitcoin: Cryptography, Engineering and Economics edited by Pedro Franco, Bitcoin Basics 101The Bitcoin Primer: Risks, Opportunities, And Possibilities by David Seaman, Understanding Bitcoin: The Liberty Lover’s Guide to the Mechanics & Economics of Crypto-Currencies by Silas Barta and Robert P.!Murphy, Blockchain by Melanie Swan, Programming the Blockchain in C# and Bitcoin Book

10. Influencers: These are the people you need to follow to get your daily dose of learning, inspiration, and innovation on your social feeds. These are the finest brains of the world in blockchain and Crypto assets:

11. Here is a Complete Crypto Guide and you can play with Hash functions here to understand how they work

12. An excellent guide on blockchain development languages by BlockGeek

13. A fantastic beginner’s guide to understand Smart Contracts

14. MOOCs: There are hundreds of courses and workshops out there to teach you crypto-currencies, blockchain and related technologies. There is a Byte Academy’s 14-week on-site program in New York that costs 10,000$, there is Oxford Blockchain Strategy Program for around 3,000$, there is ConSenSys developers program for 1,000$ and even a complete Masters (12,000$) and Ph.D. program in Blockchain by University of Nicosia. There are also quite a few specialized course providers, there is B9LabBitDegreeUdemy and Lynda; However my personal favorite is BlockGeeks; it should be your first stop. It is the best resource out there and offers courses from basics of blockchain to ERC20 tokens and from Segwit to Smart Contracts.

You can learn it all for under 200$ a year. Here is my favorite list of MOOCs you should check out:

1) I would start with Khan Academy: Bitcoin
2) Here is a programmer’s paradise with practical projects — Bitcoin Engineering @ Stanford
3) If you like to dive further, take this — Bitcoin, Altcoins & Blockchain
4) Zastrin offers good courses on Ethereum, including the one to build your own voting application
13) University of Nicosia — Introduction to Digital Currencies (One of the best and most comprehensive MOOCs available)
19) B21 Block
26) IBM Free Course on Blockchain Essentials
27) The Best course to develop a decentralized App (DApp) by BlockGeek

15. There are several good resources to learn Solidity. You may like to start from here & here, and then move to this, then this, and there is always a BlockGeek guide on the subject. Complete Solidity documentation is available from this link. Udemy offers a very good course to Learn Solidity as well. Here is a good medium post that compiles related video tutorials to learn Solidity

16. A very good guide on how to become a blockchain developer from BlockGeek and here is an exhaustive list of how to become a blockchain developer by howtotokens. And here is the ultimate index of all the good blockchain resources available on the net

No one can stop you if you like to become a blockchain developer, it will take around a year, few hundred dollars, firm commitment, a lot of patience and heavy programming practice to become one. Once you go through all or some of it, you can practice at GitCoin to see how good you can code and get paid for your work. You can also submit your profile at CrossOver and get a remote job for $100,000/year. Even if you complete half of it, send me a note and I will have something ready for you.

Ball is in your court; it does not matter where you are and how much you can afford, if you want to make at least four times higher the average income of your countrymen, this is the way to do it, at least for the next ten years.

If you want to learn more, you can follow me on Twitter or LinkedIn. If you can understand Urdu, here is my book on Blockchain and Crypto-Currencies.

For more information visit this link.
 https://medium.com/@zusmani/how-to-become-a-blockchain-developer-ba874ac05f27


Tools for Big Data

Tuesday, 20 March 2018

Are you confused about which tool to select for Big Data . Here is a list of tools used in majority. There are thousands of big data tools out there for data analysis today. Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. To save your time, in this post, I will list out 10 top big data tools for data analysis in the areas of open source data toolsdata visualization toolssentiment toolsdata extraction tools and databases.

Open Source Data Tools
1. Knime
 
KNIME Analytics Platform is the leading open solution for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist.
 2. OpenRefine
 
OpenRefine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it, transforming it from one format into another, and extending it with web services and external data. OpenRefine can help you explore large data sets with ease.
 
What if I tell you that Project R, a GNU project, is written in R itself? It’s primarily written in C and Fortran. And a lot of its modules are written in R itself. It’s a free software programming language and software environment for statistical computing and graphics. The R language is widely used among data miners for developing statistical software and data analysis. Ease of use and extensibility has raised R’s popularity substantially in recent years. 
Besides data mining it provides statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and others.
4. Orange
 
Orange is open source data visualization and data analysis for novice and expert, and provides interactive workflows with a large toolbox to create interactive workflows to analyse and visualize data. Orange is packed with different visualizations, from scatter plots, bar charts, trees, to dendrograms, networks and heat maps.
 5. RapidMiner
 
Much like KNIME, RapidMiner operates through visual programming and is capable of manipulating, analyzing and modeling data. RapidMiner makes data science teams more productive through an open source platform for data prep, machine learning, and model deployment. Its unified data science platform accelerates the building of complete analytical workflows – from data prep to machine learning to model validation to deployment – in a single environment, dramatically improving efficiency and shortening the time to value for data science projects.
 6. Pentaho
 
Pentaho addresses the barriers that block your organization's ability to get value from all your data. The platform simplifies preparing and blending any data and includes a spectrum of tools to easily analyze, visualize, explore, report and predict. Open, embeddable and extensible, Pentaho is architected to ensure that each member of your team — from developers to business users — can easily translate data into value.  
 7. Talend
 
Talend is the leading open source integration software provider to data-driven enterprises. Our customers connect anywhere, at any speed. From ground to cloud and batch to streaming, data or application integration, Talend connects at big data scale, 5x faster and at 1/5th the cost.
 8. Weka
 
Weka, an open source software, is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data set or called from your own JAVA code. It is also well suited for developing new machine learning schemes, since it was fully implemented in the JAVA programming language, plus supporting several standard data mining tasks.
For someone who hasn’t coded for a while, Weka with its GUI provides easiest transition into the world of Data Science. Being written in Java, those with Java experience can call the library into their code as well. 
9. NodeXL
 
NodeXL is a data visualization and analysis software of relationships and networks. NodeXL provides exact calculations. It is a free (not the pro one) and open-source network analysis and visualization software. It is one of the best statistical tools for data analysis which includes advanced network metrics, access to social media network data importers, and automation.
 10. Gephi
 
Gephi is also an open-source network analysis and visualization software package written in Java on the NetBeans platform. Think of the giant friendship maps you see that represent linkedin or Facebook connections. Gelphi takes that a step further by providing exact calculations.

Originally this article was written on octoparse to get more information please visit this link
https://www.octoparse.com/blog/top-30-big-data-tools-for-data-analysis/

Become a Blockchain Developer

Monday, 26 February 2018


Do you have the craze to become a Blockchain developer and want little guidance then give it a read.Over the past few months, Blockchain and cryptocurrency have been on the news, mainly because of the sky-high prices of Bitcoin. These are the buzzwords that everyone seems to talk about these days. Both have been topic of discussions on social media, offices and over tea in cafes. Everyone today isn’t giving a second thought to investment in cryptocurrency. But one shouldn’t just invest blindly in cryptocurrency, because there’s a lot of science involved behind blockchain and cryptocurrency. It is necessary to know about it instead of just jumping into the world of cryptocurrency.
Here are few books that can become your step by step guide to blockchain and cryptocurrency.

1. The Age of Cryptocurrency: How Bitcoin and the Blockchain Are Challenging the Global Economic Order by Paul Vigna, Michael J. Casey (2016)

This book serves as a guide to people who don’t understand the technicalities of cryptocurrency. The book gives a detailed background of cryptocurrency, how it came to being and the story of its origin. The book gives a summary of cryptocurrency, current players, the bootstrapping of Bitcoin, and its future scope.
The book is long and has well-researched facts about cryptocurrency up to 2014. The author of the book also talks about cultural and technological effects of blockchain technology.

2. Mastering Bitcoin by Andreas Antonopoulos

This book starts with a brief history of Bitcoin, wallets, and mining. Then it is followed by details of the development of currency. The author covers all in this book including history, working points, the clients of Bitcoin, Blockchain, Mining and Consensus as well as Bitcoin Security.
If you read this book, you wouldn’t have to research more on the currency because it has just everything about cryptocurrency that one needs to learn to be an expert.

3. Blockchain Basics — A Non-Technical Introduction to 25 Steps by Daniel Drescher (2017)

The name of the book is enough to tell how it stands out among all the books on Blockchain. The book has all the information on blockchain and cryptocurrency divided and explained in 25 concise steps with all the pertinent details.
It has limited Mathematics and no complicated jargons that makes it easy to understand the book. There’s not much technical language involved as well so the book is also an easy catch for anyone who is just genuinely interested in learning about the book. However, giving a thorough read to it can make you a blockchain and cryptocurrency expert

4. Blockchain Revolution by Don Tapscott and Alex Tapscott

Blockchain Revolution is an informative and concise read on how the blockchain can change the civilizations for good with its unlimited applications. The book talks about the broad scope of blockchain and how it can help a society prosper.
The book is all about the revolution cryptocurrency and blockchain can bring and talks about how important it is for the future of technology. This book lets you recognize the importance of cryptocurrency in this digital era.

5. Down the Rabbit Hole by Tim Lea

The book can guarantee you profit from cryptocurrency if it is read keenly. It is a very insightful read on how technological future will look like. The book is very easy to grasp because of the use of non-technical terms used by the author.
The blockchain and cryptocurrency are excellently simplified for people who don’t really know about the terms but wish to have expertise on them. 
Originally this article was written on Techjuice to get more information please visit this link.https://www.techjuice.pk/5-books-blockchain-and-cryptocurrency-expert/

How to become a Data Scientist.

Wednesday, 7 February 2018

A cheat sheet of becoming a Data Scientist for Free by Zeeshan-ul-Hassan Usmani:
  1. Understand Data: Data is useless and can (and should) be misleading without the context. Data needs a story to tell a story. Data is like a color that needs a surface to even prove its existence, as color red for example, can’t prove its existence without a surface, we see a red car, or red scarf, red tie, red shoes or red something, similarly data needs to be associated with its surroundings, context, methods, ways and the whole life cycle where it is born, generated, used, modified, executed and terminated. I have yet to find a “data scientist” who can talk to me about the “data” without mentioning technologies like Hadoop, NoSQL, Tableau or other sophisticated vendors and buzzwords. You need to have an intimate relationship with your data; you need to know it inside out. Asking someone else about anomalies in “your” data is equal to asking your wife how she gets pregnant. One of the distinct edge we had for our relationship with the UN and the software to secure schools form bombings is our command over the underlying data, while the world talks about it using statistical charts and figures, we are the ones back home who experience it, live it in our daily lives, the importance, details, and the appreciation of this data that we have cannot be find anywhere else. We are doing the same with our other projects and clients.
  1. Understand Data Scientist: Unfortunately, one of the most confused and misused word in data sciences filed is the “data scientist” itself. Someone relate it to a mystic oracle who would know everything under the sun, while others would reduce it down to statistical expert, for few its someone familiar with Hadoop and NoSQL, and for others it is someone who can perform A/B testing and can use so much mathematics and statistical terms that would be hard to understand in executive meetings. For some, it is visualization dashboards and for others it’s a never ending ETL processes. For me, a Data Scientist is someone who understands less about the science than the ones who creates it and little less about the data than the ones who generates it, but exactly knows how these two works together. A good data scientist is the one who knows what is available “outside the box” and who he needs to connect with, hire, or the technologies he needs to deploy to get the job done, one who can link business objectives with data marts, and who can simply connect the dots from business gains to human behaviors and from data generation to dollars spent.
  1. Watch these 13 Ted Videos
  1. Watch this video of Hans Rosling to understand the power of Visualization 
  1. Listen to weekly podcasts by Partially Derivative on Data Sciences and explore their Resources page
  1. University of Washington’s Intro to Data Science and Computing for data analysis will be a good start
  1. Explore this GitHub Link and try to read as much as you can
  1. Check out Measure for America to gain an understanding of how data can make a difference
  1. Read the free book – Field Guide to Data Sciences
  1. Religiously follow this infographic on how to become a data scientist
  1. Read this blog to master your R skills
  1. Read this blog to master your statistics skills
  1. Read this wonderful practical intro to data sciences by Zipfian Academy
  1. Try to complete this open source data science Masters program
  1. Do this Machine Learning course at Coursera by the co-founder Andrew Ng of Coursera himself
  1. By all means, complete this Data Science Specialization on Coursera, all nine courses, and the capstone
  1. If you lack computer science background or want to go towards programming side of the data sciences, try to complete this Data Mining Specialization from the Coursera
  1. Optional: depends on the industry you like to work with, you may want to check out these industry specific courses/links on data sciences, healthcare analytics – intro and specializationeducationperformance optimization and general academic research
  1. To understand the deployment side of data science applications, this cloud computing specialization from the Coursera and Youtube Amazon Web Services and free trainings are a must to do
  1. Do these second-to-none courses on Mining Massive Datasets and Process Mining
  1. This link will lead you to 27 best data mining books for free
  1. Try to read Data Science Central once a day, articles like this can save you a lot of time and discussion in interviews
  1. Try to compete in as many Kaggle competitions as you can
  1. To put a cherry on the cake, these statistics driven courses will help you in differentiation from all other applicants – Inferential StatisticsDescriptive StatisticsData Analysis and StatisticsPassion drive stats, and Making Sense of Data
  1. Follow the following on Twitter for Predictive Analytics: @mgualtieri@analyticbridge@doug_laney@Hypatia_LeslieA@hyounpark@KDnuggets, and @anilbatra
  1. Follow the following on Twitter for Big Data and Data Sciences: Alistair CrollAlex Popescu@rethinkdbAmy HeineikeAnthony GoldbloomBen Lorica@oreillymedia., Bill HewittCarla Gentry CSPODavid SmithDavid FeinleibDerrick HarrisDJ PatilDoug Laney – Edd DumbillEric KavanaghFern HalperGil PressGregory PiatetskyHilary MasonJake PorwayJames GingerichJames KobielusJeff HammerbacherJeff KellyJim HarrisJustin LovellKevin WeilKrish KrishnanManish BhattMerv AdrianMichael DriscollMonica RogatiNeil RadenPaul PhilpPeter SkomorochPhilip (Flip) KromerPhilip RussomPaul ZikopoulosRussell JurneySid ProbsteinStewart TownsendTodd LipconTroy SadkowskyVincent GranvilleWilliam McKnightYves Mulkers
The whole list will take 3 to 12 months to complete and will cost you absolutely nothing, and I can guarantee you that with this skills set you really have to try very hard to remain jobless. Even if you complete half of it, send me a note and I will have something ready for you.
Ball is in your court, it doesn’t matter where you are and how much you can afford, if you want to make at least four times higher the average income of your countrymen, this is the way to do it, at least for next 10 years (where we will be generating 20 TBs of data per year per person versus 1 TB of data per year per person in the last 10 years.)
I will write separate articles on Data Science Books (I’ve read 127 of those in last six months) and MOOCs (I am celebrating my 25th MOOC certification today).
For everyone else data sciences is an opportunity, for me it’s a passion
I tweet at @ZeeshanUsmani
*This article is written by Zeeshan-ul-Hassan Usmani at Kaggel, if you want to read more pls visit this link. https://www.kaggle.com/getting-started/44915