To answer this question, allow Coursenator to take 5 minutes of your life. Data Science is used to gain insights and knowledge from different types of data. It's a combination of computational and scientific thinking, tools, and some logic.
In this article, we will follow the Data Scientist with Python.
From this knowledge, your ability to get Data Science jobs will increase by 80%. Since I cannot spoon-feed you every step, you have to figure out small things by yourself.
Data Science in Marketing
In the business world, how would you sort through the purchasing data to create your marketing plan? You enforce data-driven marketing campaigns to predict customer behaviour and preferences. You can then use these insights to offer a more customized personal experience and specific audience targeting. The possibilities of using Data Science in marketing are endless. Maybe you learn Data Science and develop new methods of sorting through data that can get you profits, bonuses, promotions, and a chance to start something of your own. Just like marketing, Data Science can apply to anything you can think. In simple words, if you analyze any data you have gathered, you can find out ways to make the process more efficient and profitable.
Here are the ten expertise in Data Science and will help you choose one. Embedded content: https://https://www.coursera.org/specializations/data-science-fundamentals-python-sql
Data Science in Advertising (targeted advertising)
We all remember when Facebook (Meta) was targeted for stealing data from the public. Still, Google does it on an everyday basis, and it has our permission to do it, but have you wondered how they gather all your data and then show you targeted advertisements based on your interest/need?
The answer is data science; there is a tiny data science algorithm everywhere targeted advertisements are being shown. Since user personalization is the future of every service industry, using data science to do targeted advertisements is absolutely brilliant.
If you want to know more about this, go to this link for more information on a targeted advertisement.
What do Data Scientists do?
Data Scientists take information in the form of data, analyze it, process it and then model the information in form of valuable isnights which can be used in businesses and research.
[Here are the ten expertise in Data Science and will help you choose one][2].
Next, I will explain the process of becoming a Data Scientist.
1. Learn a programming language('Python' or 'R')D
If you don't know what Python is, I would recommend this article. You can skim over it and come back. 'R' is the same as Python, but it is mostly used in statistical analysis and graphing, whereas Python can do anything, from game development to web building to website scraping.
Component 2
You can learn Python for data science here with an additional project, and you can learn R here for Data Science with another applied learning project.
(There are many online courses on R and Python for Data Science, Contact us [Coursenator] or scroll down below to view the lessons!)
If you want to exercise your basics, I recommend this book to hone your skills until you become a beast in Python and this book in R for Data Science.
2. Learn the necessary skills
The second part of your journey to becoming a Data Scientist is to learn the basics of Data Science. There are many things you need to study, which are:
2.Machine Learning and it’s algorithms
3.Data Visualization, Manipulation and Analysis.
Component 3
You can get all these skills in the courses mentioned below, but if you want to study them in relation to data science in depth, follow these links to learn more about the courses!
Statistics for Data Science
Machine learning for Data Science
Data Visualization for Data Science
Data Analysis
Work on projects, get experience and start building your portfolio
Once you get a hold of it, you should <explore and research the following topics to get a feel of the process and the work that comes along with it. Data Science is an active, practical field of work, and to perfect your skills; you need to get hands-on experience by which you can gain actual knowledge of Data Science.
By actively working on these joint projects, you will find fundamental problems that you will face in the field and start working on your approach to solving them. It's all a game of application.
Component 4
Think outside the box and figure out where and how to apply Data Science to your activity/project/work/hobby.
“The goal is to turn data into information, and information into insight.” – Carly Fiorina
This amazing quote by Carly Fiornia explains the basics of Data Science which you will use. You turn data into information by data visualization, machine learning algorithms, statistics and more and information into insight by common sense and business insights. By working on projects and case studies, you build your online presence on sites like Kaggle, Github, Linkedin, etc. These projects will help you get Data Science Jobs.
Component 5
In the 21st Century, job recruiters rarely hire people through the old-fashioned way. Through these online sites, your projects will sway them in your direction and increase the chances of earning $100,000 per year!
You can shape your portfolio based on your interests. For example, if you like machine learning, you need projects that involve machine learning.
As I mentioned at the beginning of this article, you can also solve a business problem with Data Science.
3. Take part in coding competitions.
If you want to master this field, Hackathons are the best way of doing it. Kaggle allows participation in Data Science competitions, you will get an in-depth experience of solving Data Science, and then you will be a beast in this field of work. Here is a video on how you can enrol in a Kaggle competition.
coding
4. Get out there!
Now that you have the basics, the next step is to get out there! Start searching for companies or small businesses that need a data scientist or an intern. You can only learn so much, but if you don't get experience that lets you get a feel of the industry, you won't be able to excel; after all, that's the end goal.
There is one necessary skill that you need to have before you enter this data science field, and that is business expertise or sense because, in Data, you need to analyze it and provide insights that will help the business grow more, you can play around with data all you want, but if you don't have the business sense to increase efficiency and profits by viewing data in real-time, then it's not worth.
I'd recommend you join a startup for a few months or start something of your own, you never know what might work out, but the point still stands that there is no place better for learning and getting experience than a startup as you must take care of everything on your own.
The skill gap and the scarcity of labour are prevalent in the industry. Even the biggest and the most important tech giants have expressed their views on the difficulty.
Where are Data Scientist jobs?
They are everywhere, as Data is being used everywhere in the world and here are the top countries where the salaries are at their highest.
According to Glassdoor, Coursenator has researched this table that compares different data scientist salaries in other countries.
Screenshot 2021-11-02 141708
As you can see from the above graph, Denmark is the country with the highest paying data scientists' jobs. Still, it would help if you never forgot that every country is different. Its cost of living is additional. Its culture is different, so choosing one may lead you to miss out on another opportunity that could expose you to unique experiences. From the previous section you may have found out the answer to the question how much does data scientist make, in the next section you will find out the comparison between the countries and their respective industrial growths.
In Job Satisfaction, India ranks first while France ranks last. Denmark pays the highest while the United States is somewhere in the middle, and India is last. Here is a comprehensive analysis keeping in mind the industry growth in different countries. In terms of Industrial Growth, United States, Europe, United Kingdom, China, Canada, and India have high scope for data scientists, and the reason is listed below:
United States
Since all the tech giants are in the US, it is predicted that their tech companies will spend over 1 billion dollars to procure talent. Apple has also doubled its number of AI-skilled experts and is scouting for new talent. Since the US is the no.1 in Data Science and Artificial Intelligence, it is the best country for a data scientist; their salaries are also pretty high up at $1,00,000.
Europe
There is a shortage of digital skills in Europe, mainly AI and Machine learning. Every European tech centre like Paris, London, Berlin, Amsterdam is short of professionals. The demand for Data Scientists in Europe is so high that they are forced to recruit from outside the EU to fill the vacancies. There could also be a shortage of 2 million skilled workers in Germany, with the majority being IT professionals. The average salary for a Data Scientist in Europe comes down to $82,000, and Europe is one of the best places to live in the world so go ahead!
United Kingdom
According to specialists in recruitment, the demand for data scientists in the UK has tripled over the last five years. The rate at which it's increasing is double the rate in Canada and 20% more than in the United States. Considering the industry and the average salary of a Data Scientist in the UK, which is $64,000, it's a great place to get a job and settle.
China
China is already a superpower, and they are usually on the Top when it comes to AI. China invests in many AI-based techs like facial recognition eyewear for the police and scanners to help catch wanted criminals. But China is indifferent to other countries, with their domestic market unable to cope with the positions. A professional with five years of expertise is rare, so they are also looking to other countries for talent in data science. With the shortage of data scientists in China and the average salary of $46,400, China is a good option. As mentioned, they are always scouting for talented professionals.
Canada
This country is known for investing in ethics, policy and frameworks of AI and data science. The growth for data scientists in this country is increasing as they aspire to take the leading position in data science and AI. Since the average salary for Data scientists is $68,000 and considering the industrial growth, Canada is a viable option to apply for a data scientist job.
Our team's country saw 137,870 vacancies in data scientist jobs in 2020, an outstanding 62 per cent increase from last year. It is expected to boom double the rate in 2021. India also suffers from an acute shortage of data scientists, AI and machine learning professionals. Since India is the 3rd largest startup ecosystem globally, it witnesses 12-15% annual growth. Since data science is needed to grow a business, you can always fill a shortage of professionals!
The average salary for data scientists in India is $13,500, which is the lowest among all the above, but the growth of the data science industry will be the biggest in the world.
In the end, it's all about hard work. You need to have determination, resolve and if you follow all these steps correctly and efficiently, you will have a boost in self-confidence that will help you in your career and personal life. These are some of the best nanodegree programs which will get you certified to be a data scientist. You will get a job on the internet by which you can begin your journey of becoming a successful Data Scientist without going to a university.
If you have followed every step efficiently and consistently, you will land a job like buying a pack of chewing gum. As the metaphor defines, you may not get the best-flavoured gum the first time.
Here's an article on how to strategize while working with data.
You have to travel far (in life) and achieve that success you have been dreaming of
Here's a review of udacity's data science nanodegree on quora
Find out why udacity's programs can help you get a job. Here are some online courses in data science that will help you reach your goal of becoming a data scientist The links are in the course name only!
Data Science for Business Leaders
This nanodegree program will equip you with strategies and guidelines for solving different problems of integrating data science into your business. Learners will learn how to identify opportunities to incorporate data science in the industry and the tools and strategies to execute those opportunities.
Become a Data Scientist
in collaboration with Bertelsmann, Appen, IBM Watson, Insight, Kaggle and Starbucks, Udacity offers you an opportunity to learn the skills needed to become a Data Scientist. These are the projects that you will work on:
writing a data science blog post.
Building a disaster response pipeline with figure eight
Design a recommendation engine with IBM, using user behaviour and social network.
Data science capstone project.
Become a Data Engineer
In this nanodegree, you will learn to build data warehouses, data models, work with massive datasets and automate data pipelines. here are the projects that you will work on:
Building a data model with Postgres and Apache Cassandra
Build a Cloud data warehouse
Build a data lake
Build data pipelines with airflow
Build a capstone project with the skills you have learned.
Data Streaming
In this program, you will gain fluency in modern data engineering tools. here are the projects that you will be working on -
Optimize Chicago public transit system.
Evaluate human balance with spark streaming.
Programming for Data Science with R
By this course, Learners will get the programming fundamentals a person needs for a career in Data Science. here are the projects:
Learn how to investigate a database by going through the process.
Learn how to collect data, compute descriptive stats and create data visualizations.
Learn how to use Github and post versions of the program.
Programming for Data Science with Python
The course description and projects are identical in this course and the above one.
Data Visualization
In this course, Learners will start by building dashboards and communicating the findings to the audience as effectively as possible. here are the projects you will work on in the program-
Build a data dashboard
Design data dashboards
Build a Data Story
Animate a data Story
Become a Data Analyst
To do this nanodegree program, you need to work with Python and libraries like Pandas and Numpy. You will learn how to advance your programming skills and work with messy databases. here are the projects that you will work on -
Learn how to analyze local and global temperature data.
You will learn how to interpret the experimental results.
Using Python, you will learn to wrangle and analyze data.
You will learn how to communicate data findings.
Become a Data Product Manager
You will learn to leverage market data to amplify product development. here are the projects that you will be working on -
You will learn to develop a data-backed product proposal.
Learn to build a scalable data strategy.
You will learn to create an iterative design Path.
Here are some specializations from Coursera
Advanced-Data Science with IBM specialization
After this course, you will have a deep understanding of data exploration and visualization, advanced machine learning, deep learning and massive parallel data processing.
Skills you can acquire if you enrol:
Data Science
Internet Of Things (IoT)
Deep Learning
Apache Spark
Statistics
Machine Learning
Long Short-Term Memory (ISTM)
Data Science: Statistics and Machine Learning Specialization
Skills you can acquire if you enrol:
Machine Learning
Github
R Programming
Regression Analysis
Data Visualization (DataViz)
Statistics
Statistical Inference
Statistical Hypothesis Testing
Model Selection
Generalized Linear Model
Linear Regression
Random Forest
Data Science Specialization
Skills you can acquire if you enrol:
Github
Machine Learning
R Programming
Regression Analysis
Data Science
Rstudio
Data Analysis
Debugging
Data Manipulation
Regular Expression (REGEX)
Data Cleansing
Cluster Analysis
IBM Data Science Professional Certificate
Skills you can acquire if you enrol:
Data Science
Python Programming
Data Analysis
PandasNumpy
Ipython
Cloud Databases
Relational Database Management System (RDBMS)
SQL
Predictive Modelling
Data Visualization (DataViz)
Model Selection
Coursenator wishes you the best of luck on your learning journey
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