
Length: 8 Courses
Price: $700/person (USD)
Access Length: 6 months
Bulk Pricing: 10+ Contact Us
Instant Access After Purchase
Lecture by Recorded Video
Stop and Start as Needed
Certificate of Completion
Software Lab Included: No
Individuals & Groups
@ Your Location
This eLearning course includes these courses:
The Data Collection, Processing, and Analysis eLearning Bundle is a comprehensive master course designed to transform you into a proficient data analyst and data scientist. This bundle is a deep dive into the most sought-after programming languages and techniques in the data science field, providing over 28 hours of expert instruction in Python and R Programming.
You will gain immediately marketable skills across the entire data pipeline:By completing this bundle, you will possess a dual-language skill set in the most dominant tools of the industry, enabling you to confidently collect, clean, process, analyze, and visualize complex data sets to drive informed business decisions.
Start your journey to becoming a certified Data Science professional. Enroll now to master the essential languages of data!
Also Included - 4 Courses: An Essential Career Skills Pack with 4 courses in key areas for career management and growth, including Time Management, Digital Skills, Creativity and Soft Skills.
This course is suitable for:
This self-paced online course lets you learn independently at your own pace through Certstaffix Training's easy-to-use platform.
Have more than 10 students needing this course? Contact Us for bulk pricing.
Python is developed under an OSI-approved open source license, making it freely usable and distributable, even for commercial use. Python is a general-purpose programming language. Created nearly 30 years ago, it is now one of the most popular languages out there to use. Its popularity is particularly important in the data science and machine learning fields. But it is also a language that is easy to learn, and that’s why it has become the language most taught in universities.
Python interpreters are available for the main operating systems as well (Linux, Mac OS, Windows, Android, iOS, BSD, etc.) so it’s very flexible in where it is used. Python has a simple syntax that makes it suitable for learning to program as a first language. The learning curve is smoother than other languages such as Java, which quickly requires learning about Object Oriented Programming or C/C++ that require understanding pointers. Still, it's possible to learn about OOP or functional programming in Python when the time comes.
Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. This course is about leveraging the Python programming language and its thriving ecosystem to save yourself time and money when doing common routine tasks. Nobody wants to do boring and time-consuming tasks: days have 24 hours and you should squeeze out the most of this time for yourself - automating the boring tasks gives you back time to focus on what you really like to do. Moreover, this is also the chance for you to learn a great general-purpose language such as Python, with which you can build very cool applications both at work and in your spare time. The course is structured as an incremental learning path: you will start with a deep-dive into Python software development basics, then move on to write scripts to automate file system operations and file contents processing on your local host, then you will learn how to interact with web-based services such as websites and APIs in order to robotize the cool things that we do everyday - such as tweeting, posting to social networks, and reading RSS feeds. Moreover, you will practice how to set up a web-based services yourself in the form of web applications and in the end you will learn how to analyze and visualize datasets in order to extract knowledge.
Python is an open-source, community-supported, general-purpose programming language that, over the years, has also become one of the bastions of data science. Thanks to its flexibility and vast popularity that data analysis, visualization, and machine learning can be easily carried out with Python. This course will help you learn the tools necessary to perform data science.
In this course you will learn all the necessary libraries that make data analytics with Python a joy. You will get into hands-on data analysis and machine learning by coding in Python. You will also learn the Numpy library used for numerical and scientific computation. You will also employ useful libraries for visualization, Matplotlib and Seaborn, to provide insights into data. Further you will learn various steps involved in building an end-to-end machine learning solution. The ease of use and efficiency of these tools will help you learn these topics very quickly. The video course is prepared with applications in mind. You will explore coding on real-life datasets, and implement your knowledge on projects.
By the end of this course, you will have embarked on a journey from data cleaning and preparation to creating summary tables, from visualization to machine learning and prediction. This course will prepare you to the world of data science.
R is a high-level statistical language and is widely used among statisticians and data miners to develop statistical applications. This solution-based video will be your guide, taking you through different programming aspects with R.
Beginning with the basics of R programming, this video provides step-by-step resources and time-saving methods to help you solve programming problems efficiently. Starting with the installation of R, each recipe addresses a specific problem with a discussion that explains the solution and offers insight into how it works.
You will learn to work with powerful R tools and techniques. You will be able to boost your productivity with the most popular R packages and tackle data structures such as matrices, lists, and factors. You will see how to create vectors, handle variables, and perform other core functions. You will be able to tackle issues with data input/output and will learn to work with strings and dates.
Moving forward, we'll look into more advanced concepts such as metaprogramming with R and functional programming. Finally, you will learn to tackle issues while working with databases and data manipulation.
It seems that there is never enough time in the day. But, since we all get the same 24 hours, why is it that some people achieve so much more with their time than others? This course will explain how to plan and prioritize tasks, so that we can make the most of the limited time we have. By using the time-management techniques in this course, you can improve your ability to function more effectively – even when time is tight and pressures are high. So, by the end of the course you will have the knowledge, skills and confidence to be an effective manager of your time.
With the rise of digital transformation and technology, having a basic digital literacy is essential for all types of jobs, regardless of the industry. To stay competitive and be successful in the workplace, enhancing your digital skills should be a top priority.
The digital economy is opening up ways for everyone to be creative. It doesn’t just mean being artistic – it’s more about ideas, solutions, alternatives, incremental improvements. Peter Quarry and Eve Ash discuss ways that mental capacity can be developed, perspectives changed, group power leveraged and making things actually happen.
Soft Skills are the traits, characteristics, habits, and skills needed to survive and thrive in the modern work world. Soft skills aren't usually taught in school, but you will learn them all here in this course. Are you someone that other people in your organization and industry like to work with, collaborate with and partner with? Are you seen as a valuable asset to any new project that comes along?
This soft skills training course will teach you how to develop the skills that can make the difference between a lackluster career that tops out at middle management versus one that lands you in the executive suite. Or to wherever you define career success. So many soft skills seem like common sense at first glance, but they are not commonly applied by most workers. This soft skills training course will give you an edge over your competitors. It will also make your job, your career and your life more rewarding and enjoyable.
Public instructor-led Data Science course prices start at $275 per student. Group training discounts are available.
Self-Paced Data Science eLearning courses cost $300 at the starting point per student. Group purchase discounts are available.
A: There is no simple answer to the question of which courses are best for data science. The field of data science is vast and complex, and there are many different specialties within it. That said, there are some general principles that can guide students in choosing the right courses for their needs.
First, students should make sure that they have a strong foundation in mathematics and statistics. These subjects are the backbone of data science, and without a strong understanding of them, it will be difficult to excel in the field.
Second, students should choose courses that cover a broad range of topics. Data science is a multidisciplinary field, so it is important to have knowledge in multiple areas. This will give students a well-rounded education and prepare them for the diverse challenges they may face in their career.
Third, students should consider taking courses that focus on specific domains or applications of data science. While a broad education is important, it is also helpful to have expertise in specific areas. This can be especially useful for students who want to pursue a specific career path or specialize in a certain type of data analysis.
Finally, students should make sure to choose courses that are taught by experienced and knowledgeable instructors. Data science is a rapidly changing field, and it is important to learn from those who are at the forefront of its development. By taking courses from leading experts, students can be sure that they are getting the most up-to-date and accurate information.
Choosing the right courses for data science can be a challenge, but by following these guidelines, students can ensure that they are getting the best possible education. With a strong foundation in mathematics and statistics, and a broad understanding of the field, students will be well-prepared to pursue a successful career in data science.
A: There is no one-size-fits-all answer to this question, as the best way to train to be a data scientist will vary depending on your previous experience and skills. However, there are some general tips that can help you get started:
1. Firstly, it is important to have a strong foundation in mathematics and statistics. This will give you the ability to understand and work with complex data sets.
2. Secondly, it is also beneficial to have experience in programming languages such as R or Python. These languages are commonly used by data scientists and will be essential for working with data.
3. Finally, it is also helpful to have some experience in machine learning. This will allow you to build models that can automatically learn and improve from data.
These are just some general tips to get you started on the path to becoming a data scientist. For more specific advice, it is best to consult with someone who is already working in the field.
A: No, data science does not require coding. However, coding can be a helpful tool for data scientists who want to manipulate and analyze data. There are many different ways to analyze data, and coding can give you more control over the process. It can also help you automate repetitive tasks. Ultimately, whether or not you code is up to you and what works best for you and your team.
Some data scientists do not code at all, while others are proficient in multiple programming languages, such as R and Python. There is no one right way to do data science, and the tools you use will depend on your individual skills and preferences. If you're new to data science, it may be helpful to learn some basic coding skills. This will give you a better understanding of how data science works and how to manipulate data. However, you don't need to be a coding expert to be a successful data scientist. Ultimately, the most important skill for data scientists is the ability to think critically and solve problems. If you're good at that, you can learn whatever coding skills you need along the way.
A: There is no doubt that data science is one of the hottest fields in the tech industry right now. And with good reason – businesses of all sizes are looking to harness the power of data to gain insights that can help them improve their operations and bottom line.
But what does it take to be a successful data scientist? In addition to strong technical skills, data scientists must also be able to effectively communicate their findings to non-technical stakeholders and have a keen business sense to know how their insights can be applied to real-world problems.
First and foremost, data scientists need to have strong technical skills. This includes a deep understanding of statistics and machine learning algorithms, as well as experience working with large datasets. Additionally, data scientists should be proficient in at least one programming language, such as Python or R, and have experience using data visualization tools like Tableau or D3.js.
Data scientists must be able to effectively communicate their findings to non-technical stakeholders. This includes being able to explain complex statistical concepts in layman’s terms and creating clear and concise data visualizations that tell a story. Additionally, data scientists should be able to make recommendations on how their insights can be applied to solve real-world business problems.
Finally, data scientists need to have a keen business sense to know how their insights can be applied to real-world problems. This includes understanding the business goals of their organization and being able to translate their findings into actionable steps that can help achieve those goals. Additionally, data scientists should be familiar with common business metrics and KPIs, as well as how to use data to measure and improve those metrics.
While there is no one-size-fits-all answer to the question of what skills data scientists need to succeed, the above three skills are a good foundation on which to build. As data science continues to evolve, data scientists will need to continuously adapt their skillset to keep up with the latest trends and technologies.
Certstaffix Training provides Data Science classes near me or online, depending on the number of students involved. We offer online courses for individual learners, as well as in person classes at your office for corporate groups. Our trainers are highly experienced professionals with the expertise necessary to help you gain a thorough understanding of Data Science concepts and tools. With our courses available online for individuals or in person for corporate groups, it's easy to develop your Data Science skills. Start learning today and see how Certstaffix Training can help you reach your goals.