13438 Courses and Certifications

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Developing Data Products

Offered by

Certificate

Developing Data Products

3 Weeks
4,117

Offered by

Certificate

Data Visualization in Tableau

3 Weeks
Beginner
Free
Introduction to Data Science in Python

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Certificate

Introduction to Data Science in Python

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. 

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3 Weeks
Intermediate
1,699
Skills Covered:
Data science knowledge Knowledge of Python
Python Basics for Data Science

Offered by

IBM via Edx
Certificate

Python Basics for Data Science

Python programming and data science are highly valuable and in-demand skills. Top companies use Data Science and analysis to interpret data and make critical business decisions. Python Basics for Data Science by edX will delve into data science using Python. As this is a beginner-level course, you will learn about Python language from scratch and do not have to be a programmer.

The Python Basics for Data Science certification is a free programme that falls under the Data Analysis and Statistics category and will run for five weeks. It will enable you to learn at your own schedule and pace through video content. By the end of the training course, you will be adept at using Python language to create data science projects and be ready to collaborate with Data scientists. 

Enrol in the edX Python Basics for Data Science programme and gain basic knowledge of machine learning, programming, and data visualisation. You can also earn a sharable verified course certificate after completing the course if you took the course in the verified track by paying the fee. In the free track, you can audit the programme for a limited duration. 

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3 Weeks
Intermediate
Skills Covered:
Data science knowledge Knowledge of Python

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Certificate

Predictive Analysis for Business

The Predictive Analysis for Business Nanodegree Programme by Udacity has been designed to enable you to master solving complex problems with data through a scientific approach. The course will help you become fluent in two leading software packages called Alteryx and Tableau. Alteryx enables you to prepare, blend, and analyse data quickly, and on the other hand, a Tableau is a powerful tool for data visualisation. 

The Udacity Predictive Analysis for Business Online Course covers complex data-related concepts such as creating mental models to define business-related issues as well as visualising data to improve the performance of predictive models. Furthermore, the programme has been designed to implement and identify a variety of techniques for predictive modelling. 

In addition, the Nanodegree programme incorporates real-world projects to help you in skill-building through practical knowledge. You will also receive feedback from the network of project reviewers routinely. 

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3 Weeks
Intermediate
82,000
Skills Covered:
Tableau knowledge

Offered by

Google , New York Institute of Finance, New York via Coursera
Certificate

Reinforcement Learning for Trading Strategies

An understanding of Reinforcement learning (RL) is crucial in machine learning that looks at how gradient boosting should act in an environment to get the most rewards over time. Reinforcement learning is one of the three basic ways that machines can learn, along with supervised learning and unsupervised learning. The Reinforcement Learning for trading Strategies certification course is designed by the New York Institute of Finance along with Google Cloud and taught by Jack Farmer - specializing in training and consulting solutions, which is presented by Coursera. 

Reinforcement Learning for Trading Strategies online classes offer 12 hours of digital lessons that are intended to provide students with a comprehensive understanding of reinforcement learning (RL) and the benefits of using RL in trading strategies, as well as how RL has been used with neural networks and review LSTMs. 

With Reinforcement Learning for Trading Strategies online training students will learn more about how they can be used to look at data over time. Aspirants will be able to use reinforcement learning to build trading strategies, recognize the distinction between actor-based policies and value-based policies, and use RL as part of a momentum trading strategy.

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3 Weeks
Intermediate
3,438
Skills Covered:
Machine learning Trading skills Knowledge of equities Financial knowledge SQL knowledge
Artificial Intelligence for Breast Cancer Detection

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Certificate

Artificial Intelligence for Breast Cancer Detection

3 Weeks
Intermediate
Free
Trees and Graphs Basics

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Certificate

Trees and Graphs: Basics

The Trees and Graphs: Basics online course is a study of the algorithms and data structures associated with trees and graphs such as tree data structures, binary search trees, self-balancing trees, graph data structures with some fundamental traversal algorithms on graphs. The online program is provided by the online educational platform Coursera and the course curriculum is offered by the University of Colorado Boulder. The course consists of 10 hours of course content that is scheduled for three weeks. The educator for this online training is associate professor Sriram Sankaranarayanan from the University of Colorado Boulder. 

The Trees and Graphs: Basics is part of the ‘Data Science Foundations: Data Structures and Algorithms Specialization’ and the Master of Science in Data Science(MS-DS) degree hence this online course can be taken for the MS-DS degree. This advanced-level program enables the students to utilize flexible deadlines for convenience to complete the course and a shareable course certificate after course completion.

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3 Weeks
Expert
1,699
Skills Covered:
Knowledge of Algorithms Data science knowledge Programming skills Knowledge of Python
NP-Complete Problems

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Certificate

NP-Complete Problems

3 Weeks
Intermediate
Free
IO-Efficient Algorithms

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Certificate

I/O-efficient algorithms

The I/O-efficient algorithms online course is an EIT digital-based course instructed by Dr Mark de Berg through a wholly online platform for learning with Coursera. The entire programme runs for a duration of 9 hours offering a verified certificate. The I/O-efficient algorithms syllabus will progress through three weeks starting with a curriculum starting with an introduction, cache algorithms, replacement policies and efficient sorting.

The course will be taught in the English language with subtitles in English, Spanish, Russian, French and Portuguese. The  I/O-efficient algorithms by Coursera are planned as advanced level coursework with flexible deadlines for completion. The candidates will need to have some basic prerequisite in the area of mathematics and algorithms to be eligible to enrol for the programme.

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3 Weeks
Expert
Skills Covered:
Knowledge of Algorithms
Approximation Algorithms

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Certificate

Approximation Algorithms

Traditional algorithmic tools are often inefficient for solving various real-world algorithmic problems. For example, many such problems are NP-hard; hence, these tools can’t solve them correctly. Thus, the Approximation Algorithms certification course will make you fluent with the critical algorithmic techniques and concepts that can deal with these challenges efficiently. You can employ such techniques instead of the optimal solution; you need an approximation close to this optimal solution. 

Curated by EIT Digital, the Approximation Algorithms certification syllabus offers 100% online lessons and covers vital topics to make you an expert. These include PTAS, knapsack problems, vertex-cover problems, linear programming, load balancing, scheduling algorithms, and numerous other learnings. By covering these, you’ll become adept in finding the required approximations of a problem’s optimal solutions for solving it efficiently. 

The Approximation Algorithms online course features a renowned instructor, Professor Dr Mark de Berg. It also provides self-directed deadlines to help you learn comfortably, along with English subtitles for the programme videos. Moreover, you can also purchase the training completion certificate to access the valuable accreditation and graded assessments.

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3 Weeks
Intermediate
Skills Covered:
Knowledge of Algorithms
Automated Reasoning Symbolic Model Checking

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Certificate

Automated Reasoning: Symbolic Model Checking

The Automated Reasoning: Symbolic Model Checking certification course offers to learn through online mode. The course talks about the properties of acting systems and programs. The course can be pursued as a free programme in the audit mode, provided the students will not be able to get access to the graded quizzes, assessments, and certification. 

The Automated Reasoning: Symbolic Model Checking certification syllabus includes four weekly modules that can be completed in the time period of 13 hours. Students can also enable English subtitles in the programme. 

There are no restrictions regarding the timings of the sessions or attendance percentage since this is a self-paced programme that lets the user choose their own deadlines. The certification of the Automated Reasoning: Symbolic Model Checking online course is achievable at the end of the course if the participants successfully complete the course after taking the subscription of the programme.

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3 Weeks
Intermediate
Skills Covered:
Programming skills
Automated Reasoning Satisfiability

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Certificate

Automated Reasoning: Satisfiability

If you want to learn the applications for satisfiability tools, Automated Reasoning: satisfiability course is perfect for you. The programme uses several examples to give you a glimpse into the various scenarios where satisfiability can be applied. These examples include program correctness, scheduling problems, puzzle-solving and fitting rectangles used for printing posters. 

Besides this, Automated Reasoning: satisfiability training also offers the underlying theory of using the resolution as a primary approach to propositional satisfiability, applying simplex methods for solving linear inequalities and using the CDCL framework for scaling up big formulas. You will learn these concepts through a series of video lessons, reading material, practise assignments and graded assignments. However, the course encourages you to use the knowledge you receive and apply SAT/SMT to several other problems, such as the problems presented in the honour’s assignment.

Automated Reasoning: satisfiability certification is an online course that takes about 25 hours to complete. It is an intermediate course taught by Hans Zantema and is offered by EIT Digital. You can either join the course for free or take the Coursera membership and secure a certificate of completion.

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3 Weeks
Intermediate
Free
Skills Covered:
Knowledge of computer application
Programming Languages Part C

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Certificate

Programming Languages, Part C

Coursera provides an array of courses in diverse fields. These courses include E-learning videos, projects, community forums, peer reviews, and practice exercises. This course is being offered by the University of Washington on Coursera. 

The framework of the Programming Languages, Part C course by Coursera has been designed to give the learners exposure to the basic concepts of programming languages. This course strongly focuses on functional programming as it is important for learning how to write robust, elegant, composable and reusable programmes.

The course offers a blended curriculum which trains the participants in using language constructs effectively and designing correct and elegant programs. The coursework utilizes the languages Ruby, Racket, and ML as vehicles for teaching the concepts which will make the participants more efficient in programming in any language and learning the new ones at the same time. This course, Part C is a part of a 3- part course. The instructor for this course is Dan Grossman, a professor at the University of Washington who has been teaching programming languages at the University since 2003. He holds the J. Ray Bowen Professorship For Innovation In Engineering Education.

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3 Weeks
Free
Skills Covered:
Programming skills

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Swiss Federal Institute of Technology Lausanne via Coursera
Certificate

Functional Program Design in Scala (Scala 2 version)

3 Weeks
Intermediate
Free
Certificate

CS50's Introduction to Programming with Scratch

3 Weeks
Beginner
Free
Delivery Problem

Offered by

Certificate

Delivery Problem

3 Weeks
Beginner
6,638
Certificate

Introduction to Swift Programming

The Introduction to Swift Programming certification course by Coursera is the first course in iOS App Development with Swift Specialization, which comprises four courses. The certification course is devoted to making learners perform intermediate applications of Swift Programming. Moreover, a learner typically takes approximately 7 hours to finish, while the medium of instruction is English.

As of now, the Introduction to Swift Programming online course uses Swift 2 to teach the learners. Learners can come to the forefront of writing apps in iOS with new capabilities and features in Swift programming. After course completion, learners will become adept in memory management, syntax, object-oriented principles, functional concepts, among others.

Furthermore, the Introduction to Swift Programming training course starts at the introductory level and can be completed quickly. Another course attribute is flexible deadlines and self-paced training. The course has a six-weeks broad curriculum of lectures and activities and the candidate will be awarded a certificate at the end of the certification course.

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3 Weeks
3,369
Skills Covered:
Programming skills
Certificate

Learn to Program: Crafting Quality Code

The  Learn to Program: Crafting Quality Code programme by Coursera is a well-crafted course that focuses on teaching the skill for writing quality code every single time. Quality is a code that will run efficiently and correctly. The learners of the course will be taught to design the program, validate and code it too. The course further elaborates on how they can compare two or more programs that address a similar task. A simple and easy to understand programme that will help candidates upskill themselves for the future needs of programming.

The course will cover key features, responsible for the writing and execution of an efficient code. It will help develop an insight into the palindrome algorithms and using it to solve various problems in the programming domain. It will guide learners to apply logic and solve the most complicated issues in program writing and utilizing simple tools to solve them.

The course requires all the candidates to work on assignments throughout the course, these assignments will give hands-on experience to learners and will be essential in learning to use the concepts of this course and its applications. The Learn to Program: Crafting Quality Code course is an intermediate level course that is taught by specialists from the industry.

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3 Weeks
Free
Skills Covered:
Programming skills Knowledge of Python
Building Cloud Services with the Java Spring Framework

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Certificate

Building Cloud Services with the Java Spring Framework

3 Weeks
Intermediate
Free
Global Warming II Create Your Own Models in Python

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Certificate

Global Warming II: Create Your Own Models in Python

Global Warming II: Create Your Own Models in Python Certification Course is an elaborate depiction of all the concepts surrounding the application of Python programming for conducting an in-depth analysis of Global Warming. It provides an opportunity for candidates to work on different Python programming exercises wherein they shall explore how numerical modelling is put to use in studying climate sciences and the Earth system.

The successor course to Global Warming I: The Science and Modeling of Climate Change has been crafted for beginners in Python programming and thus provides significant knowledge of the same. During the course lectures, learners will discover easy ways to grasp the intermediate knowledge of Python syntax. This course also provides mid-course quizzes and readings to ensure that extra amount of knowledge which would benefit the students in their learning.

The course has been designed by experts from the University of Chicago under the ambit of Environmental Science and Sustainability under a further broad ambit of Physical Science and Engineering. The university has been known for imbibing new ways of thinking among its learners and thus offers them a lucid practical and conceptual experience of sparking a change in the world with the learnings.

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3 Weeks
Free
Skills Covered:
Knowledge of Python
Human Resources Analytics

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Certificate

Human Resources Analytics

3 Weeks
Free
Specialized Models Time Series and Survival Analysis

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Certificate

Specialized Models: Time Series and Survival Analysis

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.

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3 Weeks
Intermediate
Free
Skills Covered:
Knowledge of deep learning
AI Capstone Project with Deep Learning

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Certificate

AI Capstone Project with Deep Learning

The AI Capstone Project with Deep Learning certification course provides an advanced level of training to all its participants. The programme is within the reach of the students at no cost as it can be accessed for free in the audit mode. The course is made accessible to every aspirant through the platform Coursera. Students who enrol for this hundred per cent online training will be able to gain a deep understanding of AI. 

The course revolves around the topics of preprocessing data, building a model, validity of a model, etc. The programme is a part of a course named IBM AI Engineering that is also a Coursera programme and is in association with IBM. The curriculum of the AI Capstone Project with Deep Learning online course is managed by two industry experts that will help the students understand the concepts. 

The course material of the subject also provides hands-on experience through projects. Along with the projects, it includes quizzes, assignments, practises exercises, etc. The course does not have any restrictions with respect to admission eligibility criteria, deadlines, or attendance. The content of the AI Capstone Project with the Deep Learning certification syllabus is divided into 3 weeks and can be completely finished in around 5 hours. If the student is able to complete the course in the fixed time he or she will be able to achieve a certificate at the end of the programme.

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3 Weeks
Expert
3,384
Skills Covered:
Machine learning Knowledge of Artificial Intelligence Knowledge of Python Knowledge of Algorithms
Cloud Operations on Amazon Web Services

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Certificate

Cloud Operations on AWS

3 Weeks
Beginner
Free

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