No prior experience or degree is required to start a new career in the high-growth industry of data analytics. Get Google-designed professional training and the chance to network with leading businesses. There are 380,000 data analytics job openings in the United States, with a typical entry-level income of $74,000. ¹

Data analytics is the process of gathering, transforming, and organizing information in order to draw conclusions, make predictions, and make better decisions.

Gain in-demand skills that will prepare you for an entry-level career over the course of eight courses. You'll hear from Google employees who used data analytics as a springboard for their own careers. You can complete the certificate in fewer than 6 months if you work less than 10 hours each week.

You'll learn how to become a junior or associate data analyst, a database administrator, and other positions. After completing the certificate, you can apply for positions at Google and over 150 other companies in the United States, including Walmart, Best Buy, and Astreya.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx.6 months to complete: Suggested pace of 10 hours/week
  
• Subtitles: English
  
  

Coursera Rating: 4.8/5
Enroll here:https://www.coursera.org/professional-certificates/google-data-analytics

Data scientists that can analyze data and convey conclusions to inform data-driven decisions are in high demand. Anyone interested in pursuing a career in data science or machine learning can benefit from this IBM Professional Certificate, which will help them gain career-relevant skills and experience.

It's a fallacy that you need a Ph.D. to work as a data scientist. Anyone with a desire to study can enroll in this Professional Certificate program – no prior understanding of computer science or programming languages is required – and gain the skills, tools, and portfolio necessary to compete for entry-level data scientist jobs.

The curriculum comprises of nine online courses that will teach you how to use open source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning techniques, among other things. Using real data science tools and real-world data sets, you'll study data science through hands-on practice in the IBM Cloud.

You will have established a portfolio of data science projects after finishing these courses, giving you the confidence to dive into an exciting career in data science.

In addition to a Coursera Professional Certificate, you'll receive a digital badge from IBM acknowledging your data science expertise.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 11 months to complete: Suggested pace of 4 hours/week
  
• Subtitles:English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Turkish, Spanish, Persian, Korean
  
  

Coursera Rating: 4.6/5
Enroll here: https://www.coursera.org/professional-certificates/ibm-data-science

From asking the proper questions to developing inferences and reporting results, this Data Science Specialization offered by Johns Hopkins University covers the concepts and tools you'll need throughout the data science pipeline. You'll use the skills you've acquired to create a data product utilizing real-world data in the Capstone Project.

Students will have a portfolio at the end of the course that demonstrates their knowledge of the topic. Allow this course to kick-start your data science career. A ten-course data science introduction developed and delivered by top professors.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx.11 months to complete: Suggested pace of 7 hours/week
  
• Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, Spanish, Chinese (Simplified), Portuguese (Brazilian), Japanese

Coursera Rating: 4.5/5
Enroll here:https://www.coursera.org/specializations/jhu-data-science

This c specialization's five courses teach data science using the Python programming language. This skills-based specialization is for learners with a basic understanding of Python or programming who want to use popular Python toolkits like pandas, matplotlib, scikit-learn, nltk, and networkx to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques to gain insight into their data.

The courses Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in that order and before any other course in the specialization. Courses 4 and 5 can be taken in any sequence after those have been completed. To receive a certificate, you must complete all five steps.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Intermediate Level
  
• Approx. 5 months to complete: Suggested pace of 7 hours/week
  
• Subtitles:English, Arabic, French, Portuguese (European), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, Spanish
  
  

Coursera Rating: 4.5/5
Enroll here:/https://www.coursera.org/specializations/data-science-python

Do you want to learn more about data science but aren't sure where to begin? This IBM 4-course Specialization will prepare you for a job in data science or further advanced learning in the subject by providing you with the fundamental foundational skills that any data scientist requires.

This Specialization will teach you about data science and the work that data scientists do. You'll learn how data analysis can help you make data-driven decisions and how data science can be applied across fields. You'll discover that you may get a head start in the area without any prior understanding of computer science or programming languages: this Specialization will lay the groundwork for more advanced studies to help you achieve your career objectives.

You'll learn about big data, statistical analysis, and relational databases, as well as Jupyter Notebooks, RStudio, GitHub, and SQL, among other open source tools and data science programs used by data scientists. You'll go through hands-on labs and projects to master the methods behind solving data science challenges and apply what you've learned to real-world data sets.

In addition to a Coursera Specialization completion certificate, you'll get a digital badge from IBM identifying you as a data science fundamentals specialist.The IBM Data Science Professional Certificate can be earned by completing this Specialization.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 4 months to complete: Suggested pace of 5 hours/week
  
• Subtitles:English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Turkish, Spanish, Persian
  
  

Coursera Rating: 4.6/5
Enroll here: https://www.coursera.org/specializations/introduction-data-science

You will have a proven comprehensive understanding of huge parallel data processing, data exploration and visualization, and advanced machine learning and deep learning as a coursera certified specialized completer. You'll grasp the mathematical underpinnings of all machine learning and deep learning algorithms. You'll be able to apply your knowledge in real-world scenarios, justify architectural decisions, and comprehend the properties of various algorithms, frameworks, and technologies, as well as how they affect model performance and scalability.

You will receive an IBM digital badge if you opt to study this specialty and earn the Coursera specialization certificate. Visit ibm.biz/badging for more information about IBM digital badges.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Advanced Level
  
• Approx. 4 months to complete: Suggested pace of 5 hours/week
  
• Subtitles: English, Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, Spanish, Chinese (Simplified)

Coursera Rating: 4.4/5
Enroll here:https://www.coursera.org/specializations/advanced-data-science-ibm

This course will teach the learner the fundamentals of the Python programming environment, including lambdas, reading and manipulating csv files, and the numpy module. The course will cover data manipulation and cleaning techniques using the popular Python pandas data science library, as well as the abstraction of Series and DataFrame as central data structures for data analysis, as well as tutorials on how to effectively use functions like groupby, merge, and pivot tables. Students will be able to take tabular data, clean it, alter it, and execute basic inferential statistical analyses by the end of this course.

This course should be taken before Applied Plotting, Charting, and Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, and Applied Social Network Analysis in Python.

This course offers:

• Flexible deadlines: Reset deadlines in accordance to your schedule.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Intermediate Level
  
• Approx. 31 hours to complete
  
• Subtitles:Arabic, French, Portuguese (European), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, English, Spanish
  
• Course 1 of 5 in the Applied Data Science with Python Specialization
  
  

Coursera Rating: 4.5/5
Enroll here:https://www.coursera.org/learn/python-data-analysis

Python can be used to program and analyze data. Create software to collect, clean, analyze, and visualize data. The University of Michigan's mission is to serve the people of Michigan and the world by being a leader in the creation, communication, preservation, and application of knowledge, art, and academic values, as well as in the development of leaders and citizens who will challenge the present and enrich the future.

This Specialization expands on the popularity of the Python for Everyone course and uses the Python programming language to present essential programming concepts such as data structures, networked application program interfaces, and databases. In the Capstone Project, you'll design and build your own data retrieval, processing, and visualization apps using the technologies you've learned during the Specialization.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 8 months to complete: Suggested pace of 3 hours/week
  
• Subtitles:English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, Spanish

Coursera Rating: 4.8/5
Enroll here:https://www.coursera.org/specializations/python

It's impossible to escape arithmetic in data science classes. Data Science Math Skills by Duke Universiy was built for learners who have basic math skills but have not studied algebra or pre-calculus and want to master the basic math they will need to succeed in practically any data science math course. Data Science Math Skills offers the essential math on which data science is built, with no added complexity, one at a time, presenting unexpected topics and math symbols.

Before going on to more advanced content, learners will grasp the vocabulary, notation, concepts, and algebra rules that all data scientists must know.

Topics include:
~Set theory, including Venn diagrams
~Properties of the real number line
~Interval notation and algebra with inequalities
~Uses for summation and Sigma notation
~Math on the Cartesian (x,y) plane, slope and distance formulas
~Graphing and describing functions and their inverses on the x-y plane,
~The concept of instantaneous rate of change and tangent lines to a curve
~Exponents, logarithms, and the natural log function.
~Probability theory, including Bayes’ theorem.

This course offers:

• Flexible deadlines : Reset deadlines in accordance to your schedule.
  
• Certificate : Earn a Certificate upon completion
  
• 100% online
  
• Beginner Level
  
• Approx. 13 hours to complete
  
• Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Coursera Rating: 4.5/5
Enroll here:https://www.coursera.org/learn/datasciencemathskills

Production settings may not have the same requirements as development environments. Moving data science and machine learning initiatives from concept to implementation necessitates cutting-edge expertise. Your projects must be designed and implemented for scalability and operational efficiency. Data science is an interdisciplinary field that brings together domain expertise, mathematics, statistics, data visualization, and programming skills.

The Practical Data Science Specialization brings these fields together in the AWS cloud using purpose-built machine learning technologies. It teaches you how to use Amazon SageMaker to gain practical skills for deploying data science projects and overcoming problems at each stage of the ML workflow.

This Specialization is for data-focused engineers, scientists, and analysts who are acquainted with Python and SQL and want to learn how to construct, train, and deploy scalable, end-to-end machine learning pipelines in the AWS cloud, both automated and human-in-the-loop.

Each of the ten weeks includes a thorough lab created exclusively for this Specialization that provides hands-on exposure with cutting-edge natural language processing (NLP) and natural language understanding (NLU) algorithms, such as BERT and FastText utilizing Amazon SageMaker.

This course offers:

• Flexible Schedule: Set and maintain flexible deadlines.
  
• Certificate : Earn a Certificate upon completion
• 100% online
  
• Advanced Level
  
• Approx. 3 months to complete: Suggested pace of 5 hours/week
  
• Subtitles: English

Coursera Rating: 4.6/5
Enroll here:https://www.coursera.org/specializations/practical-data-science