Data Science Professional

Data Science Professional Certification

120 Hours Live Online

Multiple Simulation Exams

Student Handouts

Industrial Projects

Industry Based Trainers

Course Completion Certificate

Overview Key Aspects Skills Covered Curriculum Why LearnNLead Placement Application FAQs

Data Science Professional Certification

Know your way around the Data Science Professional Certification.

There is a rising need for qualified data scientists in the private sector, academia, and government. It provides you with the essential knowledge basis and valuable abilities to take on real-world data analysis issues through the Learn N Lead Data Science curriculum. Learn about probability, regression, and machine learning with this program that teaches you how to work with dplyr to manipulate data, use ggplot2 for data visualizations, use Unix/Linux for file organization, and use GitHub and Git for version control and RStudio for creating reproducible documents.

In each course, we utilize inspiring case studies, ask particular questions, and learn by answering these questions using data analysis and other methods of teaching. Election Forecasting, building a Baseball Team (influenced by Moneyball), and Movie Recommendation Systems are examples of case studies.

The R software environment will be used throughout the session. R, statistical principles, and data analysis procedures will all be taught at the same time to you. Learning how to tackle a specific problem can help you retain more R information, according to us.

Faculty and mentors

• Hand-picked mentors from all over the world to shape to fit the job you are aiming to cop.
• The faculty members will back the aspirant to make it to their goal.
• They will render all the industry-centric insights to the aspirant to prepare them for what coming their way

Key Aspects of Data Science Professional Certification

Check the details of Data Science Professional Certification.

Hands on Tool

Google data studio
Tableau
Seaborn
Matplot
Pandas
NumPy
Python

Audience Profile

Fresher graduates in bachelor or master’s degree
Managers
Marketing managers
Banking and finance professional
Business analysts
Analytical managers
IT professional

Scope of the course

On completion and taking up a job you will be highly qualified for higher paid jobs. glass doors state that $116,100 per year is what a data scientist makes.

Prerequisite

Basic knowledge of statistics.
understanding of programming language

Skills Covered

See which benefits you can derive by joining this program.

Understanding of data structure and data manipulation
Linear and non-linear regression models and techniques for data analysis
Data wrangling
Understanding of supervised and unsupervised learning models that includes linear regression, logistic regression, clustering, and dimensionality reduction
Mathematical expertise through NumPy
Adapt practical mastery with principles, algorithms, and application of ml
Analyse tableau and become proficient in a building covering dashboards
Concept of ML
Understanding of data visualization

Program Curriculum

An overview of what you will learn from this program.