Data Science Certification Training

The Data Scientist course provides in-depth instruction of the most in-demand Data Science and Machine Learning abilities, as well as hands-on experience with major tools and technologies such as Python, Tableau, R, and Machine Learning concepts.

With the learning of data science becomes an expert by diving deep into the nuances of data interpretation, mastering powerful programming skills, and mastering technologies like Machine Learning to take your career to the next level in Data Science. This Data Science certification course will prepare you to grab industry-ready top data scientist job roles.

What is Data Science?

Data science is a vast topic that entails working with massive amounts of data in order to find hidden trends and patterns and extract useful information to aid in better decision-making. Companies use a variety of data science tools and approaches to construct prediction models as they collect large volumes of data. Data Science courses from Edtia will help you learn all of the fundamentals from scratch.

What are the Data Science Course’s Learning Objectives?

Data scientist is one of the trendiest jobs this year. The US Bureau of Labor Statistics forecasts 11.5 million job vacancies in the field of data science by 2026, growing at a 28 percent annual pace.

Data Science certification from Edtia encourages you to master job-critical skills such as statistics, data mining, hypothesis testing, clustering, linear and logistic regression, decision trees, data wrangling, regression models, data visualization, supervised and unsupervised learning, recommendation engines, and more. This Data Scientist course includes live online instructor-led classes as well as self-paced learning videos.

This Data Science certification program finishes with a Capstone project that aims to reinforce the learning by creating an industry-relevant product that incorporates all of the curriculum's core concepts. This Data Science course will help you prepare for the role of a Data Scientist.

Who should take Data Science training?

The Data Science role requires a combination of experience, data science expertise, and the appropriate tools and technologies. It is an excellent job option for both new and seasoned workers.

The Data Science certification course is best suited for aspiring professionals with an analytical mindset from any educational background, such as: IT Professionals Business Analysts Analytics Managers Banking and Finance Professionals Supply Chain Network Managers Marketing Managers Beginners and Graduates in Bachelors or Master’s Degree

What are the Prerequisites of the Course?

Professionals who want to pass this Data Science certification course should have the following qualifications: Statistics basics are required. Any programming language's fundamental knowledge is required.

What kind of Job Opportunities are Available After the Course is completed?

You will have the ability to achieve your ideal career in Data Science as an Edtia learner who completes the Data Science certification course. Jobs that are excellent for data scientists include: Data Analyst Analytics Manager/Lead Data Scientist Statistical Programming Specialist Machine Learning Engineer

Why choose to be Data Scientist?

A data scientist is a high-ranking employee in any company. Data Scientist is ranked third among the 50 Best Jobs for 2022 by Glassdoor. Data scientists are in short supply and in great demand in today's ever-changing industry.

As a data scientist, you must be able to comprehend business problems, develop data analysis strategies, gather, cleanse, and structure the necessary data, apply algorithms and methodologies using the appropriate tools, and offer data-driven suggestions.

What You'll Learn

• Learn everything about data structure and manipulation.

• For data analysis, you will be able to recognize and use linear and non-linear regression models as well as classification approaches.

• Learn about supervised and unsupervised learning models like linear regression, clustering, logistic regression, K-NN, dimensionality reduction, and pipeline in detail.

• Use the SciPy package and its sub-packages such as Integrate, Statistics, IO, Optimize, and Weave to perform technical and scientific computing.

• Using the NumPy and Scikit-Learn packages, you may improve your mathematical computing skills.

• Master the fundamentals of recommendation engines and time series modeling, as well as machine learning principles, algorithms, and applications.

• Learn how to use Tableau to analyze data and create interactive dashboards.