How to become a data scientist in 3 months

Introduction:

Data science offers scientific methods, processes, and algorithms to determine the meaningful insights from both structured and unstructured data. Data science is a very promising field of data that provides various methods from mathematics, machine learning to process the data, handle the data, and analyze the data.

Geoffery Moore said:- “Without the big data analytics, industries are blind and deaf.”

Data science is the field used in every domain like Healthcare, Finance, Banking, Sales, Digital marketing, traveling, security, networking, etc.

Data science not only being used in private IT industries. It is also used in many government projects of AI and data science. Data science is adopting by many industries so the jobs are opening. According to the survey of Forbes, more than 20,00,000 job vacancies are coming every year for data science. Now you can imagine how data science is ruling all over the world.

If you are a data science enthusiast and want to learn data science in 2–3 months then you need to read this article. It will help you in understanding what you need to do if you want to become a data scientist.

Why data science?

There are billions of data generating every year which is mostly in the form of unstructured data. We had an older Business intelligence tool that was used for data analysis only on structured data set, but they are not able to handle unstructured and semi-structured data, so for that now we have Data science and BIg data technology.

Data science offers for collecting the data from different sources along with data mining, data management, data analysis, data visualizations, and predictive modeling(Machine Learning model). It made out the task easier and effective which we can be done in very less time. Nowadays, data is more important than anything and these data are used by the organizations to grow their business by making the decisions based on the statistics results, facts, and trends. It uses mathematics, frameworks and statistics, and science to extract the data and the information to find out the business problems and their solutions.

ref: google images

Data science belongs to many fields like information science, statistics, mathematics, and programming(Computer science) and it encompasses Machine learning, deep learning, visualization, pattern recognition, probability, data engineering, data architecture, etc.

How to learn data science in 2–3 months?

You can learn data science in very little time if you figure out the requirement that you need to follow. No one can take guarantee that you will become a data scientist in just 2–3 months, but yes “Nothing is impossible” if you want to achieve what you desired. You need to learn some basic skills of data science for becoming a data scientist.

If you have some prior knowledge of programming then yes it is very easy to learn data science as you can better understand the python programming and you need to learn Machin earning algorithms and implement those on python.

But, if you are from the non-technical background then you have to give almost 8 hours for your python practice with leaning machine learning algorithms if you want to become a data scientist, but stills you need to learn for at least 5 months. You can get a job with 3 months of learning but you can’t be a master in data science. For that, you need to keep patching and learning Machine learning with real-time projects.

Here are some points that you need to follow for the programmer and non-programmer:

1. Take some ideas from those who are already working as a data scientist and in the respective field. Different people tell you different methods, terms, and processes that will tell you about the challenge you would face so that you can prepare it earlier.
2. Some of the data scientists don’t work on big data, Spark, Hadoop, and SQL. So you need to know about what is the most required skills to learn according to that plan and proceed. Don’t get overwhelmed by thinking to learn many things, learn only key modules/skills. So you can learn Python and Machine learning algorithms with real-time projects.
3. Choose one industry to get a job into so that you can learn effectively according to the company’s requirements. It will reduce the number of topics to study and also gives an effective knowledge of the relevant domain of that particular field.
4. Only focus on the 5 pinpoints of job prospects so that you don’t need to study for all. Yes, you want to become a data scientist but you can step one step further by taking this approach and you will get your destination. If you get a job in any position you can identify the requirements of the next position.
5. Make a skill profile: Observe the responsibilities and requirements for the skills of its position and pick out to practice these skills. For example, you need to know about Python, statistics, probability, and Machine learning algorithms with real-time projects, so for three months, you need to gain knowledge about these.
6. Write your future resume according to the industrial perspective and which industry you have chosen to apply and make a proper heading of skills that would be highlighted your resume and start learning those skills.
7. Done a project that has followed the data science project life cycle that includes processes like data gathering, data mining, feature engineering, training the machine learning model, testing the machine learning model, creating a visualization, statistical testing like hypothesis testing of that model and practicing for interviews.
8. While you prepare for the interview just focus on the skills that you have written on your resume. You need to be skilled in basic python, python libraries that used for your model, statistics, probability, Machin learning algorithms and it’s real-time applications.

Yes, you can get a job in data science in 3 months you to become skilled data scientists you have to study at-least for 6–7 months.

You can learn supervised machine learning algorithms like Linear regression, decision tree, support vector machine, and k-nearest neighbor that are most important and widely used by the data scientists to make predictive models of data science.

Skills Required to become a data scientists:

The skills that mentioned above are necessary to learn data science and machine learning along with that there are some more tools and methods used by many data scientists are:

1. Programming knowledge of Python and R.
2. Statistics and probability.
3. Other mathematical functions and formulas such as Linear algebra, Matrix operations, integral, gradient descent, calculus.
4. In discrete math: Graph theories, set theory, trees, charts.
5. Machine learning algorithm: Linear and logistic regression of regression models, Decision tree, and random forest for classification models, KNN and K-means for clustering algorithms, Support vector machine for both classification and regression model.

6. The idea of deep learning and neural networks.

7. NLP and time-series for unstructured and numerical data.

8. Data analysis, data visualization, and reporting tools such as SQL, Nosql, MongoDB, Tableau, power, big data Hadoop, Apache-spark Hive, etc.

You will become a data scientist if you follow this cycle:

To become a data scientist skills and desired is required more than anything. Learning python is the very first step to learn data science and machine learning. Now industries acquiring data-driven technology from traditional working methods as we all have the data only. Industries required skilled data scientists and yes you can become data scientists if you learn with the desire. Learnbay Provides data science courses that are made according to the demand of jobs for working professionals and freshers, Join Learnbay, and get a better learning experience with the job assistance program.