Are you aspiring to develop a career in Data Science? If yes, then congratulations. Here, in this complete data science roadmap, you will learn about how and where to start with data science. The roadmap comprises 9 steps necessary for a beginner as well as an expert.
Step 1. Fundamentals of Artificial Intelligence
Today, AI is everywhere. One can understand AI as a division of computer science – a simulated intelligence. Its main goal is to develop smart machines that are capable of thinking and making decisions without human intervention. For building a career in emerging technology focused on developing a better understanding of AI.
The first thing to learn in a Data Science course is the basics of Artificial Intelligence (AI). The roadmap will avail you with a comprehensive sense of the concept of Artificial Intelligence. In this course, you will learn AI-related applications and real-world examples of AI.
Step 2. Mathematics For Data Science
Online Data Science Training includes an important subject – Mathematics. Mathematics is the basic domain of the entire process. It counts in Statistics, Linear Algebra, Calculus, etc. You must learn & understand linear algebra for developing ML models.
This course in this Roadmap will offer you some basic knowledge about matrices & other advanced operations and concepts. Hereafter, you will understand your models in a better manner & can deal with problems efficiently.
Step 3. Computer Programming
Once you gain a proper understanding of mathematics, you are ready for implementation. Implementing algorithms necessitates a deep grasp of several computer programming fundamentals & languages.
Programming languages are used in Data Science and each of these languages runs on functions or collection of codes. Python and R are the most popular computing languages used with Python. You have to gain specialization in understanding programming concepts & languages.
Step 4: Statistics with Python/R
After gaining an in-depth understanding of programming languages, move to the next big step in the Roadmap. It is learning to implement statistics with computer programming. Statistics with Python is one of the basic fundamental concepts related to it.
You have to opt for data science documentation. Here, you will learn Statistics with Python; including Bayesian inference techniques. After successfully completing this Data Science course, you will be equipped with statistical modeling skills such as linear and logistic regression and generalized linear models, etc.
Step 5: Data Visualization
Online Data Science Training programs always include data visualization. It is because it is effective and easy to understand. It is a field that necessitates you to be an expert in data analysis; i.e. qualitative and quantitative analysis.
You can opt for an online course that teaches you charts; like bar charts, pie charts, waterfall charts, box plots, etc. The course is also dedicated to teaching you Exploratory Analysis from a set of raw information
Step 6: Machine Learning
After gaining a good knowledge of visualization, you are done with all the necessary fundamentals of data science. Move towards learning machine learning algorithms.
It comprises Machine Learning & the most popular application of ML models is to develop a recommendation system. Hence, you have to opt for an online ML course. This course will familiarize you with cloud-based variations to be implemented with ML models.
Step 7: Text Mining and Analysis
Text mining & Analysis is another major step in learning Data Science. By text mining, we mean the act of converting unstructured data into structured data. This process simplifies analytics & helps in managing risks associated with any business or other sectors.
An online text mining course in the roadmap will teach you deep details about what is text clustering and categorization. You will also learn many basic NLP techniques used in that particular sector. Always keep in mind that text mining & analysis is an important skills requisite for high-paying data science jobs.
Step 8: Deep Learning
Now that you have reached this step of the roadmap, you (as a learner) are ready to introduce yourself to a more advanced application of ML – Deep Learning (DL). Deep Learning algorithms are rooted in Neural Networks. Neural Network is a structure that imitates the neurons of humans’ work. Huge layers of neural networks combine together to form a system – deep learning.
Presently, Deep learning has become the key in the field of Data Science. DL algorithms are used widely in trading, risk management, fraud detection, etc. For coming into that industry, you can opt for a deep learning specialization course.
Step 9: Big Data
As per its name ‘Big data’ comprises dynamic and complex datasets. Huge & giant companies have to manage it on a regular basis. Tracking customer demand and enhancing the user experience is not an easy task. Here comes the importance of those architecture.
In this course, you will learn about big data architecture in detail. You will also have to gain control over programming models & adjustable big data analysis. ‘Big Data Specialization’ course is a course in Data Science Roadmap that helps you to integrate and process Big Data into any software.