In today’s day and age, with the democratization of knowledge, it has become very easy to learn in-depth about any discipline. This also includes the discipline of Data Science as a whole. The most common question asked when people start in the field of Data Science is – How to Build a Career in AI and Machine Learning? The answer to this is not as straight forward especially when it is supplemented by other questions such as How can one learn AI and Machine Learning course for free from home?
MISCONCEPTIONS REGARDING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE
To answer these questions, it is important to first address some other common questions that cause widespread misconception regarding data science and its related fields such as Machine Learning and Artificial Intelligence.
Q1: What are prerequisites to start learning machine learning?
Ans: There are no prerequisites or pre-defined skills that are required in order to learn machine learning.
At the end of the day, these fields are related to Data Science and Data Science as a discipline is an amalgamation of Statistics, Mathematics, Programming and Reporting Skills along with having good business acumen. Any person starting in this filed is not expected to know it all and have to learn the remaining aspects. So everyone on some aspect of Data Science starts from scratch.
Q2: What is the basic before learning machine learning?
Ans: The basics before Machine Learning are the knowledge of datasets including data exploration and manipulation in any of the software such as Excel or SQL. However, even if one has no clue of all this, Machine Learning can be understood by understanding how data is dealt with using any of common languages such as R or Python for Data Science which are also used for running Machine Learning Algorithms.
Q3: Is machine learning only for computer science students?
Ans: Knowing computer science might help to a certain extent but again, Machine Learning is a subset of Data Science where other skills such as Statistics, Mathematics are also required. So It is not restricted to people who belong to the field of Data Science.
Q4. To learn AI, should I know data science?
Ans: Models based on Artificial Intelligence requires data in order to get trained and function properly. Thus Artificial Intelligence also can be understood as a part of Data Science discipline. Therefore, Yes, the way to AI goes through Data Science.
Q5. Do AI and machine learning involve a lot of coding?
Ans: AI and Machine Learning require coding but “a lot” can be said as an overstatement. A lot of highly complicated machine learning models as such are comprised of 2-3 lines of code. Again, the amount of coding depends on which level a model is being created. If a model is being created from scratch then the number of codes is a lot, however, if a package is being used then the amount of codes is a lot less.
Q6. Can I learn A.I. or machine learning without programming? or How to start learning AI without any computer background?
Ans: These fields are not specifically programming oriented fields so yes, people having no background of programming can also peruse it. Individuals having computer science background may benefit to a certain degree but it is not the only requirement.
Q7. What are the skills are required to learn machine learning and AI?
Ans: As explained earlier, a multitude of skills are required which includes the knowledge of data (data manipulation and exploration), programming and coding, statistics and mathematics and reporting.
With the above questions answered, we now can understand that in order to build a career in the field of Data Science i.e. Machine Learning and Artificial Intelligence on your own. The fact is that Data Science as a discipline of academic studies is fairly new and there are still not many academic institutions that provide formal degrees in the fields and as the field is evolving, the fact that people have a “My Self-Created Artificial Intelligence Masters Degree” in their closets is not entirely untrue. The question is, however, What is the best way to learn Applied AI, Deep Learning and Machine Learning? or How to learn Machine Learning, The Self-Starter Way? The answer to this is not straight forward. To learn all of this, one has to go through various Online-E Books, Websites & Blogs, Online Courses, Classroom Programs, Training institutes, On Job training etc. However, this answer leads to a range of another question which needs to be addressed.
One of the initial, basic and traditional way of knowing about any field is to read a book or two related to it. When it comes to data science, there are a lot of e-books available some of which are often free that can be read to have a good start over. When it comes to Data Science, Python Data Science Handbook by Jake VanderPlas is a good one to start with. For understanding the concepts of Machine Learning, Understanding Machine Learning by Shai Shalev-Shwartz and Shai Ben-David can be referred. When it comes to Artificial Intelligence, especially deep learning then the famous Deep Learning by Ian Goodfellow is a must.
The advantage of learning with e-books is that one is in complete control and doesn’t depend upon another individual. Also, this is one of the most cost-effective ways of learning about Data Science that too in great depth. The major issue with e-books, however, is the lack of any support. This becomes more prominent especially if the person has no prior background in the field. The way of e-book learning can especially be challenging as there is little or no help when facing a particular question. Books can answer the question but can’t provide an immediate answer to a very specific question.
E-Books, therefore, for learning Data Science can be used at a more intermediate level than at the starting stages. However, once a basic idea of the various fields of data science is achieved, books can be of great help.
WEBSITES AND BLOGS
There is an ocean of data science-related websites and blogs out there which make questions such as Which is the best site to learn machine learning and AI? much more relevant. The websites and blogs are among the most relevant source of learning and often provide a lot of practical knowledge.
Among the most common website and blogs are – Kdnuggets, Kaggle, Data Camp etc. There are other sources also such as Reddit’s or Google News blog on Data Science which form a very important aspect of Data Science related news.
There are multiple benefits of these sources which include the detail in which some of these blogs go and also the comments provided by the user that often further elaborate or provide efficient ways of performing complicated Data Science tasks. The problem with these methods again is that they are nor very dynamic and cannot address individual doubts and problems. Of course, questions can be posted on various forums but there is no time frame in which they are answered and to the extent and depth to which they are answered.
Websites and Blogs, however, remain one of the prime sources of knowledge. They cover a wide range of topics and these sources can easily be accessed using search engines, one can get to know regarding specific topics in a short period of time.
A platform where Data Science has gotten extremely famous as a subject is Online Courses. There are online courses available almost on all the aspects of Data Science especially Machine Learning and Artificial Intelligence. This again raises questions such as – Which course should I take to learn AI? or Where can I find Machine Learning or Applied AI course in India? The answer to this again is not very straight forward, however, when it comes to Artificial Intelligence then, a free online introduction to artificial intelligence for non-experts is provided by Udacity naming “Intro to Artificial Intelligence”. For Machine Learning, Coursera provides an online course “Machine Learning” which is offered by Stanford.
Among the advantage of Online Courses such as the fact they provide detailed information regarding various topics and the ease through which they can be accessed, the lack of human interaction is one of the major cause of concern. Like other non –interactive platforms, the users have to depend on the explanation provided in the online material, and if the explanation is not sufficient, the users have no option but go to out on internet searching for answers and have to be lucky enough to stumble upon an explanation that is able to make them understand the particular topic or problem.
All in all, apart from the problem of being less interactive, Online courses are a good way of starting, however, they are not “free” or “cheap” once advance concepts are to be learnt and mostly provide no credible certification upon completion of the course.
One of the best ways of starting in the field of Data Science is to get involved with an academic institution and attend their classroom programs. One of the most important benefits of going for this way is that one can attain relevant certificate that can help in getting a data science-related job or excel in the current job. Also, this method provides beginners with the much needed individual attention and can help in solving particular problems. Being a part of institutes also increase the chance of getting placed as some of them provide placement assistance.
There are certain institutions such as various Indian Institute of Management that have classroom programs related to Data Science and cover aspects of Machine Learning. There are multiple US and Europe based institutions also that provide such programs.
The biggest disadvantage of this method is the lack of availability of such programs. In order to get a place in such places, there is a high level of competition with eligibility criteria barring people from even applying. These eligibility criteria include belonging to a certain academic background to a minimum number of years of experience in the related field. Also, these courses are a costly affair and generally require full-time involvement and therefore can’t be done along with a full-time job.
The most effective way of starting or progressing in the field of Data Science is to get enrolled in a Training Institute dedicated to Data Science. Few renowned training institutes are headed by people who have already spent a good amount of time in the field of Data Science. Some of the institutions are comprised of highly knowledgeable faculty that know a great deal about Machine Learning and Artificial Intelligence.
The issues faced in learning from E-Books, blogs and classroom programs are addressed in such institutions to a good enough degree. Unlike getting information from E-Books and blogs, the training institutes have dedicated faculty that can guide and mentor individuals and can help in course correction along with providing constant updates of the current scenario and way forward. The lack of human interaction is also addressed here. Also, contrary to other Classroom Programs, most institutions provide online learning along with the classroom option that helps in increasing the chances of an individual enrolling in the course. Also, the courses provided by these institutes have less rigid prerequisites and are also less costly compared to Classroom Programs. The value of the certification and the placement assistance, however, varies from institute to institute with some having a very good reputation of providing placements and having a good value of the certificate.
ON JOB TRAINING
With the constantly changing work field, it is common for companies to conduct on the job training to keep their workforce up to date and meet the industry or client requirements. Individuals interested in the field of Data Science can opt for Data Science related On the Job Training. There are various Classes, Workshops, Training that are conducted by companies that can help individuals to know about Data Science.
The advantage of these methods includes the ease of learning, cost-effectiveness and the fact that it is done during the job and doesn’t require an individual to compromise on their job. There are, however, a range of disadvantages in this way. First things first, this method is not for freshers. Also, people who are lucky to come across such training have a chance of learning data science. Other problems include the limited knowledge provided by such on the job training as they are limited to the immediate requirement of the company. Also, companies often tie such employees in strict legal bonds making the knowledge to come at an eventual cost.
All in all, there are multiple ways of getting started in the field of Data Science. Each way has its advantages and disadvantages and in order to get the complete picture, one has to mix and match and learn from various sources. E-Books, Online Courses and Blogs are the most cost-effective methods but lack any human interaction. Classroom Programs, on the other hand, provide credible faculty but are not very cost-effective and are tough to get into. On the job training is another method however it is restricted to only those people who are working and are presented with the opportunity. The most common and famous method is to sign-up for a course in a dedicated training institute that can provide individual attention, placement assistance and has a good faculty and value of certificates, however, one has to look for such institutes.
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