These data science + data analytics programs will help you gain advanced knowledge about data 

Data science is closely related to data mining and big data, and all of these including analytics are becoming increasingly crucial with the evolution of technology for enterprise efficiency. Currently, data science consulting is more important than ever since it is helping companies grow and prepare for a better future. The foundation of data science is made of skilled data scientists who possess immense experience in domains like statistics, math, and computer science. Learning through these advanced skills through the best data science and analytics programs will help candidates ace the most crucial industry skills. Data analytics programs are important for gaining exposure to industry-related knowledge and help employers and organizations move forward with the best course of action for enterprise benefits. The data science + data analytics programs for students provide a complete guide to improving data skills in beginners as well as in professionals. In this article, we have listed the best data science + data analytics programs that students can enroll in 2022.

The Nature of Data and Relational Database Design

Offered by: Coursera

This course offers a comprehensive overview of data, various data types, designs of databases for storage of data, and the creation and manipulation of data in databases using SQL. After completing this course, the participants will learn to describe what business intelligence is and how it is different from business analytics and data science, conduct a basic descriptive statistical analysis and articulate the findings, differentiate between types of statistics. They will also learn about ETL, create an ERD that shows the progression from conceptual to logical to the physical design, and such others.

Statistics and Mathematics for Data Science and Data Analytics

Offered by: Udemy

This course provides an opportunity for the participants to systematically master the core concepts of statistics and probability, descriptive statistics, hypothesis testing, regression analytics, analysis of variance, and some other advanced regression and machine learning models like logistics regressions, polynomial regressions, decision trees, and more. This course is for aspirants who wish to build a career in data science or data analytics.

The Data Science Course 2022: Complete Data Science Bootcamp

This course will provide the students will the entire toolbox that will enable them to become data scientists. The participants can fill up their resumes will in-demand industry skills like statistical analysis, Python programming with NumPy, Pandas, Seaborn, and much more. The program will help them understand the mathematics behind machine learning, perform linear and logistic regressions with Python, and apply the skills in real-life business cases.

Statistics for Business, Analytics, and Data Science

The program provides a complete guide to statistics and data analysis concepts used in education, data science, and corporates with more than 100 problems and examples. By the end of this program, the students will land a high-paying job through the practical and theoretical knowledge of the course. The course content itself is the combination of 4-5 different available courses in the market.

Text Mining and Analytics

Offered by: Coursera in Partnership with the University of Illinois at Urbana-Champaign

This program covers the major and the most critical techniques used for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision-making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort. The students will be able to learn the basic concepts, principles, and major algorithms in text mining and their potential applications.

Intro to Analytic Thinking, Data Science, and Data Mining

Offered by: Coursera in Partnership with the University of California

This program on Analytic Thinking, Data Science, and Data Mining will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. The students will be made to review the types of business problems that data science can solve and discuss the application of the CRISP-DM process to data mining efforts. 

AI Workflow: Business Priorities and Data Ingestion

Offered by: Coursera in Partnership with IBM

This course offered by the IBM AI Enterprise Workflow Certification Specialization introduces the students to the scope of the specialization and prerequisites. Specifically, the courses in this specialization program are meant for practicing data scientists who are knowledgeable about probability, statistics, linear algebra, and Python tooling for data science and machine learning. 

Contemporary Data Analysis: Survey and Best Practices

Offered by: Coursera in Partnership with HSE University

Coursera partnered with one of the best universities in the world to offer a program that presents itself with a broad overview of the field. The creators of this course have realized by practicing teaching students that it might become challenging for beginners to put together a broad field map and oversee the picture of everything that data science and analytics have to offer for solving complex business problems. This course aims to fill this gap and provide a broader and organized focus on statistics and data analytics.

Teradata SQL for Data Science and Data Analytics

Teradata SQL has several additional extensions that make take businesses a few years ahead as compared to the present technological situation. In this course, the participants will learn SQL using Teradata, which is an ANSI-compliant vendor of SQL. The Teradata SQL skillset is easily transferable to other SQL platforms such as Amazon Redshift, MySQL, Microsoft SQL Server, and others.

Data Manipulation at Scale: Systems and Algorithms

Offered by: Coursera in Partnership with the University of Washington

In this course, the students will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against the businesses' requirements. They will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon.