One of the most popular kinds of website these days are those providing genealogy records. They help people searching for their ancestral roots. We are uncertain about who we are. We seek identity. Where do we come from? What are our human origins?

Religious view of human origins

Up to about two centuries ago, the religious view prevailed in Western culture. Then, people assumed they were created in the image of God with an immortal soul. They were conscious of their designated place, in the grand scheme of things, as somewhere between the angels and the animals. In short, this Christian worldview gave life its meaning, a sense of our human origins and an outlook people could try to live by.

However, nowadays, in our secular times, we have lost awareness of transcendence and the sense of the sacred. A few people even think humans descend from aliens who visited earth. But even if true this wouldn’t explain how aliens came into existence.

Most people give the scientific way of knowing pride of place. Consequently, the question, ‘Who made us, God or evolution?’ is firmly answered in favour of the latter. In Darwin’s theory there is no room for divine guidance or design.

“We are the only people who think themselves risen from savages; everyone else believes they descended from gods.” (Marshall Sahlins)

The Christian fundamentalists who argue for creationism do religion no favours. They have a literal understanding of the biblical account of the 7 days of creation. So they see this as factual history. (An alternative view they don’t like is that the book of Genesis is a myth conveying a useful psycho-spiritual message relevant to personal growth.) Consequently, the ‘creationists’ make bogus scientific claims. Not surprisingly, these are easily derided by anyone with any sense. As a result, it has become next to impossible for the idea of design within our human origins to gain any kind of fair hearing.

Evolution and our human origins

It seems today that Darwinian evolution is the only possible explanation of life’s start and development. However, Huston Smith in his book ‘Beyond the Post-Modern Mind‘ presents the case for further consideration of a concept of ‘great origins’.

Fossils found in the Earth’s crust show that there have been changes in the constitution of plants and animals, and with the help of radioactive and potassium-argon dating, these have been placed in historical sequence.

Moreover, higher, more complex forms of life (such as human beings) appeared later than simpler ones. All species of life on earth can be traced back through their pedigrees to the simplest forms in which life initially appeared.

Darwin proposed how all this happened saying it did so through natural selection of those fittest to survive working on chance mutations. Darwinism is popular in science because natural selection is purely mechanical and the mutations on which it works do so solely by accident. In other words, biology views the origin and development of human life as an automatic process with no room for divine providence.

Perhaps this is not surprising as all branches of science avoid any account of natural phenomena as having any design. This is because there can be no scientific instruments to observe purpose and meaning. What might be intended is beyond the ability of science to judge empirically.

Criticism of Darwinian evolution

We need to ask questions about any fossil evidence for incremental change.

“Geology… does not reveal… finely graded organic change and this, perhaps, is the most obvious and gravest objection which can be urged against (my) theory.” (Charles Darwin)

Also, there is the question about a lack of fossil evidence for intermediate forms between species.

“Evolution requires intermediate forms between species, and palaeontology does not provide them.” (David Kitts professor of geology University of Oklahoma)

A third concern is to do with non-functionality of changes that only later result in useful new body parts. How can natural selection account for the emergence of complex organs? Ones that are made of many parts that only when they work together after thousands of generations have any use for survival? In the short term what good is half a jaw or half a wing? The module of the brain that governs linguistic ability has no counterpart among non-humans. It’ has appeared in human beings suddenly in its present form.

Huston Smith points out that Darwin’s theory of evolution is rather weak but looks strong because there are no other contenders for understanding our origins.

Non-naturalistic views of human origins

I would suggest that if science has a restricted kind of knowing, then perhaps we need to re-look at other ideas for finding a sense of who we are and where we come from. The trouble with a naturalistic outlook is that it assumes that nothing that lacks any material component can possibly exist.

This way of thinking stops one from considering all sorts of less tangible phenomena – those that involve subjectivity and cannot be seen with any kind of precision, prediction or control. To illustrate, at times we can gain intuitive insight, notice fortunate coincidences, and remember dreams. In addition, we can be surprised by wonder and awe at the life force within nature. We can be willing to surrender ourselves to life’s growth and healing power.

Subjective truth may not prove anything, but it can offer reasons for what to believe. Beliefs about who we are and where we come from. And as such it can guide our decisions and conduct.

Spiritual awareness and our human origins

I would say perceiving in non-naturalistic ways is a sort of spiritual awareness. According to 18th century Swedish philosopher Emanuel Swedenborg, the spiritual inflows into the natural. The divine is spiritual, and it endeavours to flow into and enliven the natural. The divine energy is one of love wishing to share its life in human action.

Swedenborg thought that those learned people who study natural sciences are more likely to deny any divine reality due to their focus instead on natural forces. In addition he thought that for the rest of us any negative frame of mind is associated with a materialistic and self-orientated attitude. This he wrote opposes deeper understanding.

“The force or endeavour within the action or movement is, it is plain, something spiritual within something natural; for thought and will are spiritual activities, whereas action and movement are natural ones.” (Emanuel Swedenborg, spiritual philosopher)

Data science requires mastering in various fields like machine learning, R programming, Python, deep learning and many more. Among all these, one of the basic key programming languages required for every data scientist is R programming. These programming languages helps a data scientist to collect data, create visualization, perform predictive and statistical analysis and to communicate the course of results with stakeholders.

Basics of R programming language:

It is a programming language developed by Robert Gentleman and Ross Ihaka. It deals with various concepts of graphical and statistical methods. It includes statistical interference, linear regression, and machine learning algorithm, time series and much more. Detailed analysis like data reduction, correlation and clustering of data are easily done with R programming. The data handling process of R is very effective as compared to the rest. Critical programming language concepts are easily analyzed by R. It also provides large, integrated, coherent collection of transitional tools, particularly used for data analysis. Graphic facilities, flexible tools, along with well structured programs are its specialties. For exhaustive programs, C, C++ and FORTRAN are often accompanied in the run-time process.

R can be helpful in analyzing data that takes place in the series of the following steps:

1. Programming: R is an accessible and transparent programming tool
2. Transforming: It is a collection of various library tools that can help us in solving problems particularly related to data science.
3. Discovering: refining, analyzing, and investigation of the data must be done.
4. Modeling: The right model of the data is captured by R using a wide range of tools.
5. Communicating: Integrate graphs, outputs and codes to share the outputs of data.

R programming is used by numerous industries, namely academic, agriculture, healthcare, government, insurance, finance, retail, manufacturing and much more. Major companies like Google, Facebook, Microsoft, Uber, Twitter, HP, Ford, and Novartis use R multi purposes. Besides these, IT sectors, Analytics, Financial institutions and consultancy companies also use R for better functioning. Economic forecasting, behavior analysis, effectiveness in advertisements, data visualization, statistical analysis and credit risk modeling are a few of the major uses of R programming.

R provides various methods to make statistical analysis of big data simpler by using the following features:

• Non-linear and linear modeling
• Time-series analysis
• Clustering
• Interfaces and extensibility to other programming languages
• Sharable code packages

The charting capabilities and graphics of this language are incomparable. Initially, R gained popularity in the academic sector where data was to be reproduced constantly and it became a key to credibility. Reproducible work has been advantageous in business sector where chunks of data were analyzed time to time. Every tool required by a data scientist to evaluate and manipulate data is included in the R programming language.

Data science is redefining the way companies run their businesses. Learning a language like R can help you in various ways like giving the best insights of data, which eventually makes you a successful data analyst.

Data scientists are the most demanded professionals today. That is the reason why there are so many offline/online training courses and certificates available in the market. But why is this field so sought after?

These days’ manual jobs are replaced by machine learning, automation, and artificial intelligence. But to create these technological ways, one needs algorithms and models. But like all machines, they too are needed to be fed with prerequisites of data. Now data is present everywhere but in a raw form which needs to be cleaned and put in an understandable way, and this is where data science enters the scene.

WHAT IS DATA SCIENCE?

Data science is extracting relevant and important information from raw data, which in turn can be used for taking strategic decisions in business regarding customer satisfaction and retention, demand and supply forecasting, development of a new product, understand market trend etc.

Several subjects come together here like mathematics, statistics, programming and most importantly business management. Also, it involves several processes like data collection and storage, data mining, data cleaning, data visualization, machine learning, and interpretation. Each of these is a job on its own and is usually done by few people together.

SUDDEN DEMAND OF DATA SCIENCE

The number of companies offering analytics services is on a rise. Businesses from different sectors use data science in a different way, thus their usage of analytics depends accordingly. Currently, big data industry shows a 33.5% growth rate and is estimated to be of $2.71 billion dollars.

Banking and finance is the major player by generating 38% of the revenue, followed by digital advertising and E-commerce firms. The sectors which are growing in this business of analytics in the last few years are public healthcare, education, transportation, travel and hospitality, agriculture etc.

USES OF DATA SCIENCE IN DIFFERENT SECTOR

Almost every other sector is emerging on the analytics scene, but some of them have already started using it for their strategic advancement, like:

• Agriculture: used for forecasting demand, predicting weather patterns, predicting the price of crops, forecasting the supply.
• Manufacturing: used for knowing the demand and supply of raw materials, managing inventory, keeping a record of foremen and workers.
• Transport: used for deciding quick routes, flight plans, managing logistics of shipments, finding a cost-effective route, estimating delivery dates.
• Healthcare: keeping and analyzing health reports of patients, estimating several rates like of child mortality, malnutrition, the need for hospital beds or facilities etc.
• E-commerce: used for optimizing their websites, recommending systems, providing customer service, warehouse and inventory management, keeping track of customers and sellers.

Overall all these sectors use data science for increasing one’s business value by taking timely decisions and solving analytical problems with efficiency.

HOW TO BE A DATA SCIENTIST

To be a data scientist one should have mathematical, programming and business skills. Mathematical and technological skills are needed for cleaning, exploring and data model building tasks. Whereas business skills are needed for communicating the results to the management and for understanding the industrial requirements.

You can be mathematics graduate, a software student, a programmer or even a post-graduate in economics; you can pursue this profession with a good certification course and relevant training.

What Data Science is all about?

In the simplest term, Data Science is the combination of Data Mining and Computer Science.

Data is being generated continuously ever since the first computer was invented. Initially, companies depended on Data Mining which simply meant generating new information. But in today's environment, websites and apps are not just pamphlets, or notice boards or online informing tools. They are now a medium for millions of users to come together and share their experience. Users are now interacting with the websites, creating content, commenting, liking, researching etc. And all this is resulting in the creation of a huge amount of data which the companies are looking forward to exploiting in order to add more values ​​to their products.

In 2010, the term Big Data was coined for such a large amount of data present around us, and it paved the way for the rise of Data Science, which can draw insights from the massive unstructured datasets to support the businesses. Data Science, in the present and coming times, is about collecting, analyzing, and modeling of data. The most important part, however, is its applications such a Machine Learning, which has made it possible to make machines more accurate through a data-driven approach, and Deep Learning, which has become a class of Machine Learning which is transforming our everyday life and the way we experience things.

Jobs of Data Scientists in Industries

• Collection: The most important job of a Data Scientist is to collect the data from various sources.
• Exploration and Transformation: The structured and unstructured data has to be cleansed and transformed in order to get rid of anomalies present in the data.
• Analytics: This is the core part of the job. Based on transformed data, the Data Scientists try to understand the metrics like what the users are doing or looking at and why they are leaving, and then provide a logical solution like what can be done to engage more users and give them a better experience.
• Learning and Optimization: A / B testing allows Data Scientists to perform experiments on various models and check what models work the best.
• Representation and Visualization: The whole task is not about creating advanced models, but to keep things simple in a way that customers and others can understand.
• Artificial Intelligence and Machine Learning: It is the last part of the task where Data Scientists use complex algorithms and machine learning principles to improve the performance of machines on a particular task.

What Can You Learn From Online Training on Data Science?

Data Science is all about using statistics, creating codes, developing models, and eventually, solving problems. To achieve this goal, the training focuses on giving students in-depth training of the following tools:

• Hadoop, MapReduce and Spark are used for the purpose of handling data.

• SQL programming language is used in programming and designing a database system.
• Python is the most powerful language in Machine learning.
• R and Excel are helpful in analytics and data modeling.
• Other important tools are SAS, Minitab and XL Miner.

The online training covers all the important concepts mentioned above, along with giving students the opportunity to work on live projects. Placement assistance is also available to help students find jobs at leading companies after the training is completed.

Roberto Denti, the Founder of Quantum Art International, in association with Massimo Pregnolato, Head of Pavia University’s Department of Medicinal Chemistry, Italy, is now promoting an international art competition entitled ‘Creativity and Antidote for Human Survival’ as being an integral part of the 21st Century Renaissance.

What they do not know is that the Director of the Sustainability Research Institute in Australia has just now received an extraordinary assessment of their work, based upon the research of world famous philosophers of science. This assessment provides indisputable evidence that their work is bringing about the rebirth of Plato’s lost science that the Great Italian Renaissance failed to do. Their Antidote for Human Survival is now of great global importance.

Both Denti and Pregnolato are fully aware that paintings can contain true 3D stereoscopic images, as the artist Salvador Dali predicted. They are aware that in the 21st Century paintings are appearing that demonstrate dramatic 3D images. Neurologists are now studying this to understand its evolutionary significance. The rebirth of Plato’s lost science to prevent unformed matter emerging from the physical atom, from the perspective of the Korean crisis, certainly warrants immediate international investigation. Their human survival antidote information was found to express the scientific sustainability of Plato’s educational system.

That system was based upon arithmetic, plane geometry, solid geometry, astronomy and harmonics. Plato’s Republic refers specifically to plane geometry being associated with evolving visual and auditory spiritual perception. He stated that plane geometry was not to be used for practical purposes but only to elucidate the mind’s relationship to the workings of an infinite, ethical universal purpose.

The reason that this science is lost is because it describes the workings of a holographic universe, which is in complete denial of the mechanistic worldview held by Einstein and modern science, that all life in the universe must be destroyed in obedience to the second law of thermodynamics.

During the Italian Renaissance, Leonardo da Vinci insisted that Plato’s spiritual plane geometry was false. He incorrectly stated that the plane surface of a painting could never contain true 3D images. This mistake corrupted the attempt to rediscover the lost ethical Greek atomic science needed to avoid the destruction of civilization by atomic weaponry.

The Israeli scientist, Guy Deutscher’s 2010 book of the year ‘Through the Language Glass’ revived the colour perception theories of William Gladstone the Prime Minister of Great Britain, which were rejected by the 19th Century’s Great Darwinian Debate. From Deutscher’s research a new neurological science emerged.

Immanuel Kant’s description of an ethical, spiritual, electromagnetic field evolving within the creative, artistic mind, derived from Plato’s search for a spiritual ethic as distinct from mechanistic science.

Following Deutscher’s discovery, Denti and Pregnolato’s crucial work provides the world’s only visual evidence validating the new medical science. The 1955 Russell-Einstein Manifesto proclaimed the threat to humanity posed by the development of nuclear weaponry and called for world leaders to resolve this problem. While their attempt failed, Denti and Pregnolato’s antidote discovery provides the crucial information that is essential to achieve that objective.

Search Engines

Data science definitely plays a larger part in our everyday life today. In fact, it has deliberately made our lives easier than in the past. For example, when someone does not possess knowledge of a particular word or topic, the first thing they do is turn to a search engine. 'Google' being the most commonly used search engine of all times. This has become an everyday thing, and it couldn't be made possible without the support of Data Science in the respective field. Not only Google, but also other search engines, namely – AOL, Ask, Yahoo and Bing implement the usage of the algorithms of data science for dishing out the best possible results in a matter of milliseconds. It is estimated that data of about 20 petabytes is processed by Google on a daily basis.

Detection of Fraudulent Activities

Debts as well as losses occur in large numbers in companies each year. However, with the implementation of Data science in the finance sector, the losses and debts have been reduced to some extent. The banking companies have come to learn over time to divide the data as well acquire it through the past expenditures, the customer's profiling, etc. along with other variables necessary for analyzation of the chances of defaults and risks. It has also aided them in pushing their products of banking in accordance with the purchasing power of the customer (s).

Medicinal / Drug Discovery.

The process of discovery of drugs is full of complications and is inclusive of several disciplines. It takes long lengths, extending up to even decades of testing and then the discovery of a particular drug for a particular disease / ailment. However, since the arrival and use of data science this process has been reduced in length. Along with this, the expenditure has also gone down and a lot of time is also saved which would otherwise be wasted.

Through the implementation of learning algorithms and data science, one can introduce a perspective for each step starting from the beginning screening for drug compounds to predict the success rate based upon the biological factors.

The purpose of these algorithms is to predict what kinds of effect will the respective compound cause in the body, with the help of advanced level of mathematical simulation and modeling rather than the lengthy experiments carried out in the lab. Computer models and simulations of them are created in the role of a biologically network that makes the predictions of the future easier to make along with more accuracy in the outcomes.

Customer Support

With the implementation of data science, we can help promote healthier lifestyles for patients, encouraging them to make healthy decisions. Along with this, it enables the doctors to concentrate their focus to the cases that are more critical. By simply describing one's symptoms, and asking questions they can receive the key information regarding their medical condition. With the help of apps, one can be reminded of taking medicines on time and these also provide healthcare support to patients.

Manufacturing is one of the many sectors which can benefit immensely from data science. Every industry is somehow related to the manufacturing industry as they all depend on goods, either to sell or to manufacture a final product.

Data science in manufacturing

There is a huge amount of data present today regarding products, demand, supply, consumer preference, manufacturers etc. The main reason why all this data can be helpful is that the industries can now harness the knowledge so that they can satisfy the needs and demands of their customers without any delay or lack of quality.

Data science can be helpful regarding manufacturing in many ways like:

• Demand forecasting
• Customization of the products
• Detecting any kind of anomaly in the supply chain or product
• Predictive maintenance
• Automating the entire process of purchase and order
• Offer different personalized services to the customers and clients

Sourcing of data for the manufacturing industry

Data is everywhere and all these data are precious if used properly. In a value chain, one can find several types of data like sales, supply, maintenance data etc. Other than that, even the consumers are producing a lot of data because, today, many of the appliances and device are installed with sensors which give data about the product and its behavior. This is the best way to know about the quality of the product and to know how and where there is an anomaly in the performance.

There is also a lot of data present in the plant histories and ERP systems as they are a great source of data for production capabilities, operations, and processing. Maintainance logs and machine readings, asset data, manuals etc. are also good sources of data. Certain types of data can be collected by using surveys, call centers, focus groups etc. as the means to collect data.

Benefits of using data science in the manufacturing industry

There are many ways big data can be implemented in manufacturing and as a result, one can get many advantages out of it like:

• Optimization of operations

Using big data properly means the industry can increase the overall responsiveness of the manufacturing sector, use the capacity of resources to the fullest, get a clear picture of the costing, and also take quick decisions regarding the operations.

• Reduce risks in the supply chain

Using data from all around the globe on different political, economic and climatic issues, one can design the supply chain pattern so that there can be an effective working chain keeping in mind all other contingencies.

• Reduce costs

Using predictive analysis of the data, the industries can now invest smartly on projects which are valuable and also focus on buying equipment and machinery which will reduce the cost of the production and enhance the overall performance thus cutting costs throughout.

• Improve the quality of products

Having enough data regarding customer insights on a certain product and how a certain product behaves, one can use that to improve quality. Data science is also helpful in customization of the products according to the consumers and their demographics.

• After sales service

Today, marketing is no more product oriented or manufacturer oriented, it is entirely customer oriented as it is not enough just to sell a product, but also to make sure that the customer gets quality service even after sales. Using predictive analysis and customer services, one can up the quality of the customer-seller relation.

As science continues to build up vast amounts of knowledge, this question might sound misplaced. Of course there are still many wonderful discoveries to be made, but I am concerned that many people have the idea that science is completely objective and has somehow made rubbish of Christianity. Well, has it, or is it still missing something? What am I getting at?

• ADVANCE

The goal of the methods of science; the patient investigation, the experiments, the close evaluation of findings and their interpretation, is to yield the advance of knowledge. But any advance is necessarily provisional, as vast further areas still remain and how they all fit into the puzzle. The field of scientific work covers many branches, which may be classified in three broad groups; Physical sciences, Life sciences and Earth sciences.

This article offers an overview on how secular science reads reality, especially our humanity and how it views origins, both of the cosmos and of life. Everyone has ‘spectacles’ – their own way of seeing, and all research includes a vital component of the researcher bringing their own existing knowledge to bear upon their new field of work. What we may overlook is that a philosophy of science controls how new work will be understood as it provides the interpretive framework or lens through which that work is then viewed.

• INTELLECT

One very interesting area is the study of intelligence and what sort of marks may characterise it. This has led some secular scientists to propose that in view of the astonishing complexity in many living creatures and in the arrangement and balanced characteristics of the cosmos, that a purposeful intelligence is the best and clearest explanation for these features. They are not calling this intelligence ‘God’ – that for many is a large step too far. But they are ready to acknowledge that given our own intelligence, our personal powers of reason, including logic and mathematics that the remarkable marks of complex information, especially in the DNA codes of life and the astronomical complexity even of a single cell organism that evolutionary theory cannot account for it. The probabilities are so stacked against it all happening by natural selection and mutations that it would never happen. And yet we find that the proposal of intelligent design is still being labelled ‘pseudoscience’ on the Wikipedia website. This is extraordinary considering that even Richard Dawkins could find no way of disproving that our own human civilisation was not a computerised sub-reality set up by super-intelligent beings.

• WONDER

However, all atheists have seen some of the Creator’s magnificence, wisdom and power in the created reality. They have seen how their own minds and comprehension of reality are a faint reflection of an infinite intellect, but they don’t they want to recognise it, because they are running away from reality – from the living God himself. From the original high and unspoilt position, our humanity has fallen into rebellion, as clearly revealed in the biblical book of Genesis, and we are left naturally trying to stifle and squash God’s signature in ourselves and in reality. Actually, this rationality in the universe and in us first gave rise to modern science. For without that sense of true correspondence of reality with our own minds there is no exploration or discovery of meaningful information in the first place.

But the naturalistic philosophy of the atheist rules out God because that is its major starting assumption. Then it calls intelligent design ‘pseudoscience’ but needs to protect the bias of its own position by calling it ‘science’. So, is there any scientific evidence upon which to base a materialistic and naturalistic philosophy of science? None – it is a belief system immune from proof, grounded in a false ‘faith’ – a philosophy that is a far better fit for ‘scientism’.

• SUPREME

What’s going in this clash of different ways of interpreting reality? Quite simply, due to that original moral rebellion against one Almighty Creator, large numbers of people still see marks of a Creator’s wonderful wisdom, but ‘suppress the truth’ (Romans 1:18) and leave it out of their reckoning because it challenges them and their naturalistic worldview. Others, however, have become willing under the sheer weight of such clear pointers to accept that there is a supreme intelligence behind all things.

This often raises the common objection, ‘Well, that intelligence isn’t up to much is it, when even our lesser intelligence can see so many flaws, so much illness, disease, sorrow and death? Why wasn’t ‘it’ able to do a better job?’ Yes, the approach is still hostile and perfectly fits the Genesis account, as it refuses to accept that when God had finished the original creation it was all perfect and flawless (see Genesis 1:31).

Once you begin to see that the present world system of which we are a part has been justly judged because of human rebellion, then you may see the clear explanation that all the sorrow, grief and death follow from the original rebellion. Meanwhile the theory of evolution has failed to account for the emergence of even the simplest organism, let alone the astonishing variety of living creatures.

• LIFE

So, just what is ‘science’ missing? Those who do not wish to see anything other than their fixed naturalistic view are suppressing and holding down all the rich wonder that is still clear, even in the now spoiled and decaying creation. But, that sense of true wonder invites us to consider and embrace the far greater wonder of a Creator’s loving kindness in sending his much-loved Son, Jesus Christ into this world to bear the just judgement of the sinful rebellion of all those who will turn and trust him for a free forgiveness and the gift of eternal life.

Today, will you consider what is beyond the narrow limits of naturalistic ‘science’ and see the glorious immensity of all that you are missing – the living God himself, and then ask him for what is freely offered; the gift of a new life in Christ that reconciles you to God the Father and which makes you a ‘new creation’ in Christ (see 2 Corinthians 5:17).

An Emerging Course: Data Science Certification

DATA SCIENCE, the most happening and desirable job of the 21st century, has surprisingly little talent available in the job-market. Data Scientists are deemed the crucial assets of an organization because of the intense demand for skills such as machine learning, deep learning, statistical techniques etc., which are the key areas of expertise owned by a data scientist. Expertise in these sectors helps a company leverage the power of data and ensure that decisions are prompt, correct and objective. It also helps the company to stay relevant, modern and efficient in its use of available data. Business communications and methodologies have come a long way in recent decades, and organizations need to regroup to help the company stay agile, adaptable and focused on the larger picture.

According to recent research, around 200,000 data scientists are needed in the industry right now which makes it evident that the industry is soon going to face a shortage of highly skilled professionals. But this shortage can be reduced or avoided if IT experts undergo data science certification on-line.

The question arises as to why would one waste his/her time and money on this course? Would the benefits accrue for themselves or only for the industry?

The benefits involved are tremendous. The list is huge but it is a fact that undergoing a data science certification can help you to shape your career and perhaps switch to a more lucrative and fulfilling one.

Why Should One Pursue Certification In Data Science?

This course can be undertaken by anybody – be it an experienced, skilled professional, a fresher, or one who wants to build new skills and learn new techniques.

Some of the most important benefits include:

1) On-line Certification does not serve as an interruption in your current job or earning level. Classes can be attended on-line according to your own comfort and convenience as they are available 24×7.

2) Certification can help you to shape your career and to reach greater heights. It involves building your skills and enhancing your knowledge-base in data science. This makes you eligible for employment in leading companies that face talent shortage in this sector, and are in a dire need of engaging certified professionals. Salary prospects are not a constraint, as pay packages are showing an upward trend driven by such unparalleled demand.

3) On-line Data Science Certification gives you credibility and it will position you as a fortune builder of big corporate giants, start-ups, small and medium organizations etc. It helps you to add business value to the organization by gaining useful insights and taking smart and logical decisions that are influenced by expertise and tactics not by instincts or intuition.

If you want to have an edge or to stand out from the crowd, choose well-established, reputed data science certification programs that have universal recognition. Certifications serve as a proof of your competency and help the industry to measure your knowledge and skill base. If you have the perfect mix of skills and knowledge, then you can easily a demand high salary. The right certification in data science can help you to build your career.

Isaac Newton’s infinite universal first principle theories of gravity were derived from ancient Greek science. Today these principles can demonstrate that Einstein’s quantum mechanical worldview had been based upon the false assumption that Newton believed that the mass of objects in space was the first cause of gravity. Einstein’s quantum mechanics led to the Big-Bang theory of the universe expanding from nothing, which appears to be quite absurd. In 1952 the Nobel Laureate scientist, Erwin Schrodinger, referred to a multiverse that to his audience might have sounded like a lunatic idea, but nonetheless his prize-winning mathematics argued otherwise. The existence of multiple parallel universes is now at the centre of great controversy. The 2007 Nobel Laureate, Steven Weinberg, pointed out that if they did exist then the Big Bang theory was doomed.

A multiverse universe is considered to be able to communicate information electromagnetically to our universe’s outer membrane. The ancient Greek scientific explanation of gravity, that Newton referred to in his 28th Query Discussions, began when a father of science, the philosopher Thales, associated the nature of gravity with a sexual demiurge to cast seed into the cosmic egg. We can now play around with the concept that once the ‘seed’ penetrates the universal membrane, it begins the growth of its baby at the speed of the Big Bang. Furthermore, the Greek science about this process was considered ethical if it was about giving birth to a healthy, compassionate offspring.

That ethical purpose was held to be accomplished by nurturing and harmonic female information, resonating from planetary movement being echoed by all living atoms in the universe. This process was referred to by the ancient Greek Science for ethical ends as Wisdom Through Beauty associated with the Music of the Spheres.

Einstein’s mechanistic world-view held that the universe would eventually be destroyed according to his understanding of the universal laws of thermodynamics and entropy. However, Newton’s first principle logic was about the living process within an infinite universe. We can use such first principle logic to reason about the existence of ethical emotional thought. For example, infinite fractal mathematics is used to model biological systems.

The Electromagnetic Golden Age of Danish Science showed how this may be accomplished. Firstly, its goal was to find an ethical motor to make Faraday’s electromagnetic motor a child’s toy by comparison. In the image of the demiurge to cast seed into the cosmic egg, the human sperm propels itself toward the ovum by an electromagnetic motor driving its tail. Upon entering the ovum the electromagnetic liquid crystal structure of the ovum’s membrane transforms the sperm’s motor into a centriole. This centriole then electromagnetically charges the first bone formed in the embryo, the sphenoid bone. Attached to the sphenoid bone is the Vagus nerve, the basic building block of human compassion. Hence, we are able to update the ancient 3rd Century BC Greek Science for ethical ends.

Scientists have deduced that the nature of the communication between our universal membrane and a parallel universe is spoken in a mirror-image electromagnetic language. The philosopher of science, Immanuel Kant, in his distinction between artistic aesthetics and ethical artistic wisdom, along with his contemporary, Emmanuel Levinas, argued that artistic evolutionary wisdom is a spiritual inner creative vision induced by an ethical mirror-image electromagnetic field. The electromagnetic geometrical shape taken by the cell at the point of cell division employs electromagnetic mirror-image field properties. These properties prevent the present dysfunctional information belonging to our thermodynamic world-view from being transmitted to the replica cell. This dysfunctional information now belonging to the epidemic transmitted by the mass production of information and communication devices that is now causing incredible social damage can be considered a form of cancer. The antidote lies in a completely new world-view beyond the limitation of the Big Bang theory.

Art, in particular stereoscopic art, plays an important role to help in realising Kant’s electromagnetic universal purpose. The artist, Salvador Dali, experimented with stereoscopic art in order to explain the existence of a more profound future scientific culture. By viewing many paintings of the 21st Century through asymmetrical electromagnetic stereoscopic glasses, Salvador Dali’s message about a future Science-Art culture becomes immediately visible. New Science-Art technologies have made this possible. From such information an antidote to the present dysfunctional stereoscopic epidemic, transmitted by the mass manufacture of information and communication devices becomes feasible.

By programming a computer with the ancient Greek spiritual wisdom, previously forbidden because it did not conform to present science’s demand for our extinction, we can gain freedom from the dictates of the universal thermodynamic heat death law and quickly generate a rigorous human survival blueprint simulation.