List of Online Courses and Certifications

The Data Wrangling and Ingestion using Python Online Course is offered by the FutureLearn portal in collaboration with Github and endorsed by Coventry University, U.K. This training course is the third installment of the Data Analytics Using Python programme available at the portal. During this course, learners will gather knowledge about Python functions and how to use python in the data analysis process. Along with this, candidates will explore the use of SQL in data analysis and gain insight into the fundamentals of databases using SQL. 

The Data Analytics Using Python: Data Wrangling and Ingestion syllabus is divided into four weeks in which candidates will get deep knowledge about Python and its use in managing the different databases of the organisation. This course will be instructed by Ed Marks with English as a medium of instruction. 

To apply for the Data Wrangling and Ingestion using Python Training Course, candidates must visit the provider’s official website and register.  For other details regarding the course such as admission process, fee structure, etc. Candidates are advised to go through the entire article given below.

The Python Packages: NumPy and Pandas Dataframe Training Course is the second edition of the Data Analytics Using Python training programme that is offered by the FutureLearn portal in association with Github and endorsed by Coventry University, U.K.  In this course, learners will learn how to apply the fundamentals of Python programming in a project. Also, candidates will gain knowledge about data ingestion and how it is done by using python. Through this course, candidates will develop knowledge for data analysis and use python programming language more effectively.

The Python Packages: NumPy and Pandas Dataframe Certification Syllabus is divided into four weeks where candidates will develop their analytics skills using python and explore data ingestion with CRISP-DM methodology. The course will be instructed in English by Ed Marks. The Python Packages: NumPy and Pandas Dataframe Online Course will be conducted in online mode through various interactive sessions, doubt sessions, etc. Candidates who are interested in taking admission to this course must visit the FutureLearn official website and register. To get all details related to the Python Packages: NumPy and Pandas Dataframe Course, candidates must go through the article given below.

The Data Analytics and Python Fundamentals Certification Course is offered by the FutureLearn portal in collaboration with Github and endorsed by Coventry University, U.K. Through this course, learners will learn the fundamentals of statistics and its application in data analytics. Also, candidates will learn to use Python in data wrangling, ingestion, and use of advanced data analysis tools and techniques such as data mining and machine learning.

The Data Analytics and Python Fundamentals Online course is a part of the Data Analytics Using Python programme. The course will be taught by Ed Marks with English as a medium of instruction. The course syllabus is divided into four weeks which will focus on the key aspects of data analysis and the use of python. Candidates who are willing to take admission to the Data Analytics and Python Fundamentals Training Course must visit the FutureLearn portal and register. All details related to this course are given below in the article. Candidates are advised to go through the article carefully.

The Python Functions, Files, and Dictionaries certification course by Coursera introduces user-defined functions and the dictionary data structure. In the curriculum, you will learn about global and local variables, optional and keyword parameter-passing, lambda expressions, named functions, and Python’s sorting function as well. You will also learn how to pass in another function as an input, to control the sorting order. 

The course also includes a final project, where you will have to read social media data from a file, write out .csv files, and compute sentiment scores. The course covers chapters 10 to 16 of the ‘Fundamentals of Python Programming’ textbook, which is available for free as the programme’s accompanying text.

Suppose you have already taken up the Python Basics course, and want to expand your knowledge of Python. In that case, the Python Functions, Files, and Dictionaries training is ideal for you. Both these courses are geared towards new students of Python programming. Those who have had some exposure to Python, need a refresher, or wish to dive deeper into it, will also get benefitted from this course.

The Wiley Certified - Python Programmer certification course is created to explore the working of packages, installing and operating Integrated development environment, type conversion, Performing operations on variables, The course consists of various extensive hands-on work, assignments, and live training.

The Wiley Certified - Python Programmer certification By WileyNXT offers every possible knowledge of basic programming language as python is a popular general-purpose programming language used by both small and large-scale Applications. Due to its large standard of libraries such as Pandas, Numpy, Matplotlib, Python is adopted by a huge number of large-scale applications. 

The Wiley Certified - Python Programmer online course encourages students to learn about various libraries of python which have easy readability & multiple paradigm support including functional, procedural, and object-oriented programming styles, the libraries consist of various types of built-in modules which help in different types of data input and output operations with a wide range of functionalities in the modules available in python libraries.

The Introduction to Data for Business Leaders online course is offered by the online educational platform FutureLearn and is developed by ‘The DataLab’ which is a centre for innovation in data and AI. The online training is scheduled for four weeks with three study hours every week.

This online certification course equips the learners with the understanding of data and values derived through data in organisations that cause improved business outcomes. The ‘Introduction to Data for Business Leaders’ programme is about recognising and categorizing data and changes within an organisation. Here the candidates are taught to describe the organisation’s data maturity aided with strategies to find ways to improve its standards to strengthen business management. It assists in understanding and calculating the investments needed from within the organisational setup to drive the business and value systems forward.

The ‘Introduction to Data for Business Leaders’ online certification course can be done at the learner's convenience using the advanced course materials. The candidates will gain knowledge as they discuss ideas with their peers and learn along with Craig Paterson who is the strategic advisor and coach.

The Distributed Computing with Spark SQL certification course is a 14 hours course. This course is available on the educational course platform Coursera, and the syllabus is curated by the University of California. Also, this course is part of the main programme, Learn SQL Basics for Data Science Specialization. 

This Distributed Computing with Spark SQL training course is made for candidates with some ideas, and information about SQL. This Coursera programme will be great for students who want to step ahead in their data journey. All 4 modules developed for this course are intertwined among themselves. In the end, when all 4 modules are learnt, the candidates will have learned many ways related to Spark SQL, and ways to construct reliable data points.

The Data Informed Decision Making Certification Course is a 4-week program. The Institute of Product Leadership is in charge of awarding the certification for this course and teaching the syllabus.

Data Informed Decision Making certification training enables learners to establish their credentials as professionals in the field of data science with decision-making skills in addition to receiving early appreciation from their peers.

Data Informed Decision Making Certification by the Institute of Product Leadership, Bangalore helps boost career profiles and improve professional equity.

Part six in the series of programs on the same domain the online course on AI Workflow: AI in Production by Coursera can be persuaded by students who have an earlier and strong understanding of - NumPy, IBM Watson studio, Python, Pandas, Linear Algebra, and Descriptive and inferential statistical concepts. 

The online course focuses on the models of productions that are aimed at streaming media companies. The course will be introducing the students to the core concepts of IBM Watson Learning. The online program over the period of 17 hours covers the topics of - data analysis, visual recognition, machine learning, and hypothesis testing,  bias detection, NLP and others. The AI Workflow: AI in Production certification syllabus will be covered by professionals.

Many firms use Artificial Intelligence to optimize procedures and boost productivity. Digital Skills: Artificial Intelligence course explains AI in action, its benefits and drawbacks, and studies the ethics of responsible AI, and Digital Skills: Artificial Intelligence certification is completely developed by Accenture's professionals which FutureLearn offers. Digital Skills: Artificial Intelligence syllabus includes three weeks of duration, two hours of weekly study, extensive learning resources, and unrestricted access to the course for people who wish to build and analyze how AI breakthroughs may affect their work and increase their understanding of artificial intelligence.

The Introduction to Machine Learning certification course is offered by Duke University. It will help you know your strengths and apply your skills in the most efficient manner to get work done. It will give you additional knowledge that will make you more confident in your work and perform better at your workplace or start your own business. 

The course will give you a brief overview of machine learning models like natural language processing, logistic regression, convolution neural networks, and multilayer perceptrons, while also explaining how these models can be put to use for solving technical problems in various industries like medical, image recognition, and text prediction. 

It is a combination of practical as well as theoretical knowledge about Machine learning, that will provide you with a framework for understanding how you can implement data science models and machine learning algorithms. The  Introduction to Machine Learning Training Course will allow you to work on a real-world hands-on project that is required in the fast-developing technological world. 

The Machine Learning Rapid Prototyping with IBM Watson Studio certification course will be allowing the students to work in the emerging technologies of AI. The syllabus is included in the online course Machine Learning Rapid Prototyping with IBM Watson Studio by Coursera. The online programme is  100% online programme and the course is having a duration of eight hours. The Machine Learning Rapid Prototyping with IBM Watson Studio certification syllabus includes the chapters of- Classification Prep Demo, Regression Prep Demo, Multi-armed Bandit Approach, Demo Classification: Making Changes to the Models, Automated Data Preparation, DAUB Algorithm, The model selection problem and others.

The course 3D Data Visualization for Science Communication gives an introduction to 3D data visualisation and emphasises on cinematic design and science communication for attracting a wide range of audience. The candidates will build visualisation literacy, they will be able to write and create their own visualisations. The course is provided by The University of Illinois at Urbana-Champaign which is a top university when it comes to teaching, public engagement and research.

The course will cover a wide range of topics under 3D Data Visualization for Science Communication which includes an introduction to scientific visualisation, critiquing visualisation, computer graphics, visualising pipeline, 3D geometry, computational resources, programming, data representation, virtual coordinates, transformations and attributes, data artefacts, pre visualisation, camera design, image artefacts, to name a few.

This course will be purely taught online using lecture videos, quizzes, discussion forum and reference reading materials. The candidates will be expected to clear all the quizzes and tests included in the course to be eligible for being certified in the course if on the event of purchasing the certification.

Introduction to Data Science in Python is an online certification programme provided by the University of Michigan and available on Coursera which is one of the five specializations of Data Science. Thus, this course must be pursued prior to the other course in the specialisation i.e Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, and  Applied Social Network Analysis in Python. Learners will be able to study data science in Python in greater depth with the tutelage of experienced instructors. 

Introduction to Data Science in Python Certification, accessible on the platform of Coursera, will expose the candidates to basic techniques of Python programming such as lambdas, reading the CSV files, and the NumPy library and python programming environment. By enrolling in the Introduction to Data Science in Python Online Course, the learner will develop the capacity to deal with tabular data and manipulate it along with running the fundamental inferential statistical analyses. 

Introduction to Data Science in Python Certification by Coursera will shed light on data manipulation, and the process of using the group by and pivot tables in an effective fashion. Introduction to Data Science in Python Certification Syllabus will help the students explore the cleaning techniques using the popular python pandas data science library and usage of the Series and DataFrame for data analysis and many more. 

If you have already learnt about the basics of Algorithms, you are now ready to take the next logical step into more complex algorithms and problem-solving. The idea behind this Advanced Algorithm and Complexity course is to teach you how to build upon the algorithm basics and utilize new ideas. In this course, we will be starting with network flows that are employed in the typical applications like detecting disjoint paths, optimal matching, and flight schedules along with a few other surprising applications like the segmentation of images in computer vision.

In the next segment, we teach linear programming with its application in allotting and optimizing budgets, Portfolio optimization, finding a diet that is cheap and satisfies all the requirements. Further, we discuss the inherent hard problems that have no perfectly good solutions known (and neither are likely to be found) and how you can solve them in practice. The course finishes with a slight introduction to the streaming of algorithms that are used, most heavily in Big Data Processing. These algorithms are mostly designed to process huge data sets without being capable of storing even a single dataset.

We are witnessing and adapting to the fourth industrial revolution, Industry 4.0, powered by Big Data and AI. At the global level, data integration has become highly essential for organisations and businesses to achieve global competitiveness. With the prevalence of Big Data all around, it becomes highly relevant to explore the underlying information and reap optimum rewards. In this scenario, data science and analytics enable decision-makers and business leaders to understand, manage and utilise data effectively.

R is a free, open-source programming language that is widely used by data scientists and analysts for developing software and applications in a data science setting. R offers tools and techniques for data analysis, statistical computations and data visualisation. R is available to use on various operating systems and is widely recognised for its extensibility, which allows developers to develop and distribute their own software as add-on packages. These features make R programming an ideal choice for data science experts and data analysts to utilise R in a variety of fields and areas.

The R Programming Environment online certificate course offered by Johns Hopkins University via the Coursera platform aims at providing useful knowledge of R Programming Language to data scientists, data analysts and data science experts to efficiently work in data science settings. This 100% online programme is of intermediate level and the first course in the Mastering Software Development in R specialisation.

By taking up the Specialized Models: Time Series and Survival Analysis online course the students will be working on the ways to identify the modelling challenges that are common within the domain of time series data. The course will further be helping to understand the process of how trends are gauged and accessed in a time series of data. In the Specialized Models: Time Series and Survival Analysis certification syllabus the students will be covering chapters on- Identifying Nonstationarity, Common Transformations, Smoothing Moving Averages, Time Series Smoothing, Deep Learning Notebook, Survival Analysis and Censoring and others. The online course on Specialized Models: Time Series and Survival Analysis by Coursera will be elaborating on the domains of “time-series data” and will be working on its applications.

Performing data science with Azure Databricks requires about 3 weeks to complete. Microsoft is the associate of Coursera in designing and delivering the online programme. This certification is a sub-programme in the five-course umbrella programme of the Microsoft Azure Data Scientist Associate (DP-100) Professional Certificate. As experienced and expert professionals prepare the programme at Microsoft, the learners can have intensive training on data science processes with Azure Databricks, Databricks Azure, Azure Spark and Apache Spark. 

Perform data science with Azure Databricks Certification Course, offered by Coursera, an intermediate-level programme. The learners of this programme should have experience with using  Python for data exploration and machine learning models with open-source frameworks, such as TensorFlow, Scikit-Learn and  PyTorch. Perform data science with Azure Databricks Certification by Coursera can be taken and covered at the learners’ pace. 

The Python Project for Data Engineering certification course, developed by IBM Skills Network and taught by Ramesh Sannareddy, a subject matter expert in data engineering, and Joseph Santarcangelo, a Ph.D., data scientist at IBM, is made available by Coursera, which is intended for participants who want to evaluate their expertise by using web scraping and extracting data with APIs, all with the help of numerous hands-on experiments.

Python Project for Data Engineering online classes provides 9 hours of prerecorded learning materials with an emphasis on assisting participants in obtaining the knowledge necessary to apply fundamental Python abilities by utilizing various data collection and data processing strategies. The Python Project for Data Engineering online course covers subjects such as Watson Studio, Jupyter notebooks, and API functions as well as demonstrates how to extract data from various file formats, change it into particular datatypes, and then load it into a particular source for analysis.

Business and analytics go hand in hand in the technologically advanced era. It is crucial to know about making data-driven decisions with the help of business acumen and raw data. Incidentally, the Introduction to R Programming and Data Analytics programme is designed to help the candidates with the same. It is an online, short-term training that houses nearly 15 hours of interactive lectures. Candidates have to attend weekend sessions. 

The IIT Kharagpur Introduction to R Programming and Data Analytics course is offered by Vinod Gupta School of Management, IIT Kharagpur, India. The instructors of the course will comprise faculty members of IIT Kharagpur, along with industry leaders who will deliver the lectures. The curriculum involves live lecturing sessions, case study discussions, hands-on practices, and live problems for better and immersive learning outcomes.

Moreover, the Introduction to R Programming and Data Analytics online course has a follow-up course: Data Analytics with R Programming. It will be conducted post the conclusion of this one. The programme is aimed at developing the candidates into introductory data scientists and adept data analysts who have a thorough understanding of the applications of analytics in managerial positions.

Microsoft Azure Databricks for Data Engineering is a Microsoft-offered course for intermediate-level learners, including data engineers and developers. The programme will enable you to learn and make aware of Microsoft Azure Databricks. Microsoft Azure Databricks for Data Engineering Certification Course is the eighth course in the 10-course Microsoft Azure Data Engineering Associate (DP-203) Professional Certificate offered by Microsoft. 

Offered by Coursera, Microsoft Azure Databricks for Data Engineering Training is entirely provided in online mode. The course will provide you with a deep insight into Microsoft Azure Databricks and related technologies and concepts such as Microsoft Azure Databricks documentation and characteristics of Azure Databricks. You can complete the Microsoft Azure Databricks for Data Engineering Certification by Coursera within the minimum duration of 21 hours. The eligible students are expected to have an understanding of data processing languages like SQL, Python, or Scala and knowledge of data architecture patterns and parallel processing. 

The course of inferring causal effects from the observational data offered by the platform of Coursera is free of cost course. The enrolled candidate can get a certificate for this course after paying a fixed amount according to the guidelines of the Coursera platform. The duration for this course is 5 weeks. This course is taught under the guidance of experts from the University of Pennsylvania. The E-certificate is available after the completion of this course.

The enrolled candidates will be provided with all the quizzes, assignments, video lectures, web links for books and references. As this course is free of cost and online, it is easily accessible for all the sections of society. Financial aid is also provided. The course of inferring causal effects from the observational data is highly recommended for all the students, teachers and researchers who are interested in this field. Financial aid is also available for all learners who cannot afford the fee. Total 33 percent of people started a new career after completing this course and 29 percent of them got career benefits after pursuing this course.

Taking the Introduction to Graph Theory certification course will provide you with useful insights into how engineers design integrated circuits and how GPS systems find shortest routes. You will also learn why a political map can only be coloured using a few colours and how biologists assemble genomes. The course curriculum includes the Ramsey Theory, which proves that complete disorder is impossible in an extensive system.

Additionally, the curriculum for the Introduction to Graph Theory certification course will cover a wide variety of graphs, including Airlines Graphs, Directed Graphs, Bipartite Graphs, and more. You will become adept in applying various algorithms to solve real-world problems via practice exercises and hands-on projects. 

Moreover, National Research University Higher School of Economics and the University of California and San Diego are offering the Introduction to Graph Theory programme jointly. As a result, candidates will be able to find better career opportunities upon course completion. 

The Introduction to Graph Theory online course is highly suitable for professionals working in the IT sector and IT aspirants.

Here most standard combinatorial settings are addressed in the Combinatorics and Probability course that can help answer questions of this nature. In particular, this course focuses on improving the ability to differentiate these settings from algorithmic problems in real life. This will assist candidates to apply new knowledge in practice. Besides that recursive counting technique that is necessary for algorithmic implementations is also addressed here.

The Combinatorics and Probability course is part of Introduction to Discrete Mathematics for Computer Science Specialisation. There are total of five courses in it and Combinatorics and Probability is the second one. The language of computer science is known as Discrete Mathematics. In many areas including data science, software engineering and machine learning, one needs to work fluently. Via a fun approach, candidates are introduced to this language. Firstly they will solve several interactive puzzles that are specially designed especially for this online specialisation. Then actual solving methods and significant ideas will be introduced to them. It is sure that candidates will gain a deeper understanding in this way and will appreciate the beauty of the underlying concepts better. Programming examples, projects and problems are integrated into the specialisation in order to get the knowledge closer to IT applications.

Developing a comprehensive insight into the level of understanding of artificial intelligence (AI) and how to distinguish between reality and hype Artificial intelligence is the modelling of human intelligence processes by machines, especially computer systems. 

The Artificial Intelligence: Distinguishing Between Fact and Fiction course explains how to learn different elements of human intellect and differentiate between the claims and existing realities of AI. The Artificial Intelligence: Distinguishing Between Fact and Fiction certification was developed by Coventry University, which received five QS Stars for Teaching and Online Learning, which is offered through FutureLearn. Artificial Intelligence: Distinguishing Between Fact and Fiction training is a comprehensive programme that comprises two weeks of open-level digital lessons, operates entirely online with an unlimited membership and teaches about the characteristics of human intellect as well as the reality of AI.

The Data Manipulation at Scale: Systems and Algorithms online course by Coursera is the first step in the Data Science at Scale Specialization series. The University of Washington offers the certification course in collaboration with Coursera.

The Data Manipulation at Scale: Systems and Algorithms online certification course aims to teach the landscape of relevant systems to the students and how these systems are evaluated along with the principles on which they rely. Students will also learn the context of data science as well as the history, skills and challenges that come while working with data. Moreover, students will get hands-on experience in learning how to structure a data science project. 

Additionally, the Data Manipulation at Scale: Systems and Algorithms class programme is a self-paced learning course so that students never have to worry about missing a class. At the same time, the course is 100% online so that they can learn from the comfort of their home. The students will be awarded a shareable certificate after completing the course, which can be shared on professional platforms. 

The University of Alberta and Alberta Machine Intelligence Institute offer the Sample-based Learning Methods training programme in conjunction with Coursera. An intermediate-level course, the programme is spread across four weeks, with intensive modules on reinforcement learning. The course will also help you understand how learning from experience can help you attain optimal behaviour. 

The Sample-based Learning Methods certification course will help you understand concepts like Temporal Difference learning, Monte Carlo strategy, exploration, dynamic programming, and more. Moreover, the certification course will provide you with a chance to apply TD algorithms, Expected Sarsa, Q-learning, and more.

Instructors will conclude the Sample-based Learning Methods online course by looking at how algorithms can combine model-based planning and temporal difference updates to fast-track learning. Additionally, the certification course offers the flexibility to learn at your own pace in your own time and set your own deadlines. 

You will also receive a combined shareable certificate from the University of Alberta and Coursera, upon completion of the Sample-based Learning Methods course.

The course Fundamentals of Reinforcement Learning certification course is offered by Coursera by collaboration with the University of Alberta to make the aspirants skilful with machine learning and applications of Artificial Intelligence. The course is free to enrol and can access all the course materials free of cost. Therefore aspirants can use the opportunity for growing their career with a course completion certificate and increase the chances of hiring.

With the digital connection over the world, Business Intelligence over decision making is made essential in organizations. Decision making increases the prosperity of the business. Therefore the use of decision making with Artificial Intelligence and machine learning became most popular when the programme comes into existence. Organizations are looking forward to candidates who are skilled in this type of Artificial Intelligence, Robotics, Machine learning and, the Internet of things (IoT) as well

Coursera is the digital platform to learn the concepts that are offered for free. Candidates can learn throughout their lifetime and can avail of certificates after completion of the Fundamentals of Reinforcement Learning Training course. 

Machine Learning With Big Data is an online certification programme administered by the University of California San Diego to help the students explore machine learning with big data concepts. Machine Learning With Big Data  Certification Syllabus, developed by Mai Nguyen, the Lead for Data Analytics, and Ilkay Altintas, the Chief Data Science Officer, will give the students a clear understanding of strategies of machine learning for the analysis and exploration of data. 

In the Machine Learning With Big Data Certification Course, administered by  Coursera, the candidates will learn to build machine learning models with numerous algorithms and tools as well various concepts of big data. Machine Learning With Big Data Certification by Coursera is the fourth in six programmes of the Big Data Specialization. 

Getting Started with SAS programming course certification is for the learners who want to acquire skills and gain knowledge about SAS programming. This course is helpful for learners who are just beginners. The SAS programming language is a system programming language which is operated for statistical analysis. It can easily be used as common spreadsheets and databases for better understanding of the contents. SAS programming language is most commonly used in the commercial market and is open-source software. 

SAS stands for Statistical Analysis System. It is a software suite developed to ease statistical and commercial market analysis. SAS programming can easily process complex data and give out various insights that help in better decision making or predict possible solutions for the problem.  SAS is a very powerful analytics programme for various organizations who needs an urgent solution from their data. SAS provides a bunch of analytics solutions and helps by providing industry knowledge for easy access to the solutions.