Data Science Bootcamps Memphis, TN

Every business gathers data, whether it is information from sales, how their business is functioning, what their employment status is, what direction their marketing efforts should head, how reports can be delivered to stakeholders, and can be used in many other ways. What a business does with data can become a pivotal element in a business strategy. Data science is about how a business captures, analyzes, maintains, and processes data to understand and raise a company’s value. Data science is also about the technology and design choices to build from what is gathered that will move a company forward in a scalable, reliable, and reproducible way.

For many decades, knowing how to gather and what to do with data was imprecise as it relied on what people. As technology advanced, and information flooded in, it became harder to know how to manage data, let alone synthesize and produce valuable insights and predictions. As computers became commonplace in business, storage of valuable information became automated and more precise to calculate and extrapolate what that data meant. Additionally, it was often humans that entered data into computers manually for many decades, contributing to human error. Businesses were able to function with these results, but not optimally. As more software was created related to data processing, analyzing information became more precise, efficient, and in real-time. With the rise of machine learning, even more advanced ways of data gathering and analysis are on the rise, but it’s still people-driven at its core. This is where data scientists come into the picture.

The goal of a data scientist is to make all of the data they’ve cleaned up into manageable sections to present the information to stakeholders in a way that’s easy to understand and apply. The information each department receives from data is used to make informed business decisions and automate systems. Technology advances fast, so tech pros are finding ways of advancing the ability to keep up through automation. This is where the field of machine learning comes in, but these early days mean professionals are still in charge. The field of data science is growing as fast as advancements in software and machine learning occur, and as even more information is identified and processed. Because of all that is involved in this field, data scientists are more in demand than ever, making them some of the most valued professionals in business today.

Data science is an interdisciplinary career combining scientific methods, algorithms, and systems and extracting information and insights from large masses of unstructured data. It uses techniques and theories drawn from mathematics, statistics, computer science, information science, and domain knowledge. The information data scientists need first comes from designing specific programs that fit their needs. Some data science professionals code the software used by others in the field, often tailored to one specific company. The programming element of data science includes pattern recognition, signal processing, data mining, machine learning, and modeling.

The information-gathering-specific software written by data programmers goes towards advancing the next step in the process: other data science specialists who focus on reading what the information gathering software reports. Those professionals then need to know how to look at what data is most important for which function the reports will serve.

The mathematical focus of data science is on probability, statistics, linear algebra, and calculus to determine whether a test is statistically significant. Business acumen rounds out the primary parts of being a data scientist, enabling communication with business leaders to turn findings into actionable insights.

The end goal of a data scientist is to condense raw data into manageable sections, presenting a sleek report backed by hours of hard work to stakeholders. Data scientists’ reports allow business leaders to make informed business decisions and automate workflow systems. As a result, they are often heralded among the business’s most valuable employees.

Although many entering the data science field have strong backgrounds in coding, math, statistics, or other related careers, it isn’t always necessary. Data science bootcamps are perfect for those changing careers or expanding current skills for a lucrative move up the ladder. Many choose to look at data analytics first to determine how much coding they’d like to do, and some bootcamps focus specifically on that area. There is a major difference in the rate of pay a data scientist can earn. For those with basic coding skills, some bootcamps lead the student through the data science-specific coding right from the start, ensuring they are getting a field-specific education during their bootcamp.

Memphis Careers for Data Science Bootcamp Graduates

The great news for those entering a data science career in Memphis is that they won't have a hard time finding the job they want. It’s also a fantastic choice for those who want to work in a specific industry, such as healthcare, finance, aerospace, manufacturing, machine learning, and all other business sectors since every entity relies on data.

Data science is an interdisciplinary field that combines scientific methods, algorithms, and systems and extracts information and insights from large masses of unstructured data. It uses techniques and theories drawn from areas of mathematics, statistics, computer science, information science, and domain knowledge. There are positions for those who code the programs that process data, those who analyze and make predictions from the data they receive, and for a variety of types of data scientists who focus on even more specific areas.

The mathematics that professionals use in the field involves applying probability, statistics, linear algebra, and calculus to determine whether a test is statistically significant. Expertise in coding in languages such as Python, SQL, and statistical-specific software for the area a professional is in is necessary for data scientists and can be learned through training in bootcamps. Business acumen is another core job function of being a data scientist, making it possible to communicate effectively and clearly to business leaders, translating their findings into concise insights.

Although many entering the field have strong backgrounds in STEM, it isn’t always necessary. A data science bootcamp can help those serious about switching to a related career, or who want to move up the ladder quickly in their current job. Since bootcamps are investments that require less money and time, graduates can apply their skills faster than those who return to school to pursue additional degrees. During these fast-paced sessions, students in bootcamps have the advantage of networking with others in their field and most provide job coaching skills.

With the cost of living lower in Memphis than in some other areas, the high salaries in the field of data science provide a great opportunity to live more than comfortably. Grand mansions are easily within reach and homes in the suburbs come with plenty of space both inside and out. Those looking for a more central home with less upkeep than a large home can find funky loft-style living near downtown that provides plenty of access to restaurants. Memphis still capitalizes on its reputation as the home of a dynamic traditional music scene. It is considered the birthplace of rock ‘n roll, the home of the blues, and a hidden gem for those who are about to break it big time into national fame. Tech pros with long days frequently surprise audiences with alter-egos as musicians who jump up on the stage for open-mike amateur nights. This release in the form of music has been a long-standing tradition, and twelve clubs in the Memphis area offer a chance for anyone who wants to express their passion for music.

With the high salaries that go along with Data Science professions, it’s no surprise that those in the field enjoy excellent lifestyles in Memphis. Typical salaries for those in data science careers include Machine Learning experts, at around $111,000 a year, and Data Scientists, who make an average of about $119,000 annually.

In-Person Data Science Bootcamps in Memphis

Data science is a tech-based field, and learning the skills it takes to go into any path in the industry is available by attending online data science courses. Virtual learning can be live or on-demand, and there are a large variety of choices for prospective students, from beginner-friendly explorations to fully immersive bootcamps that put graduates directly in line for a career. Data science boot camps and courses can be found at the data science bootcamps page presented by Noble Desktop, the creator of this tool.

Virtual Data Science Bootcamps

Virtual coding and data science bootcamps allow students to attend from anywhere, perhaps their home or in an office. The bootcamps are immersive, comprehensive, and hands-on. Since these bootcamps are live, students have their questions answered in real-time and can even share their computer screen with the instructor if they’d like. Virtual data science bootcamps range from coding skills to boost a data scientist’s career to specific certificates and bootcamps in data science.

Those who want to pursue data science in the financial world can attend Noble’s FinTech Bootcamp, which covers the coding needed for a career in financial technology. The curriculum includes examining the possibilities that Python offers for this field in data science, finance, and machine learning, SQL to query databases, and machine learning to understand topics such as WACC, NPV, and IRR. Graduates will have a project to include in their professional portfolio upon completion.

There is a Python Developer Certificate that provides a head start for those heading towards data science. This certificate includes one of the basic languages that data scientists should have: Python. The course begins with Python basics and then incorporates dictionaries, custom functions, and sorting algorithms. Students learn object-oriented programming, work with APIs and get an overview of web databases using SQL. Topics also covered include an introduction to Django, a web framework used for back end web programming, and Django REST, used in work with images, authentication, and API endpoints.

The Python for Data Science Bootcamp offered by Noble Desktop is an excellent option for those who want to delve deeply into the arena of data science and entirely prepare for a career upon graduation. This is an immersive, comprehensive course in which students learn how to apply their knowledge in real-life job situations. In this bootcamp, students pick up Python fundamentals and move into real-world data sets. They learn how to clean and combine data, as well as generate useful statistics and visualizations. By the end of the bootcamp, students will utilize linear regression to extrapolate data and make predictions.

Another option is the Data Science Certificate. This certificate prepares students for entry-level data science and Python engineering positions upon completion. The first section of this intensive program teaches the programming skills necessary to manipulate databases and perform various levels of analysis on data. The course then continues into specific requirements of the profession, using Python programming fundamentals and using Numpy, Pandas, and Matplotlib to analyze data. Students explore the three main data science libraries and how to create predictive models from the data using machine learning packages such as Sci-Kit Learn.

Students can earn a Python Machine Learning Bootcamp that allows graduates to enter the field of data science as entry-level professionals when combined with other languages they’ll need to know. Python is the central programming language students learn and then apply to data science, machine learning, and automation. Students become proficient enough to manipulate databases easily and perform various levels of analysis on the data gathered. Next, students learn how to work with Numpy, Pandas, and Matplotlib to analyze data, which are essential skill-sets for all data scientists. The next portion of the certificate highlights the importance of reading and writing complex queries in a database. The final part of the certificate allows students to use Python to automate everyday tasks such as aggregating, updating, and formatting data.

Noble Desktop also has a Python for Data Science and Machine Learning Bootcamp. This all-encompassing learning experience focuses on a specialized skill set that is in incredibly high demand in every tech field. The bootcamp begins with linear and logistic regression and progresses to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. Important statistical concepts are presented, such as bias and evaluating the performance of machine learning models.

Data Science Classes in Memphis

While deciding if a bootcamp is a good fit, or if someone would like to have a glimpse at what data science is about, curious prospective students can look into taking data science classes. Most classes are less than thirty hours, and there are even courses that can be completed in a day. Additionally, since classes are online, there are plenty of options to take from numerous schools.

SQL Level 1 is an eight-hour live online course open to beginners and provides students with foundational skills in three core topics: Relational Database Management Systems (RDBMSs), SQL code, and Microsoft SQL Server. Queries covered in SQL Level 1 include wildcard filters and multi-table queries with inner and outer joins. SQL Level 2 is a live online continuation of SQL Level 1 (also a prerequisite). Students find data that meet specific search criteria using views, subqueries, math functions, and logic statements in this course. Both courses help fulfill prerequisites often found in data science bootcamps.

Python for Automation provides foundational knowledge for those going into any tech professional and often fulfills the prerequisite for data science bootcamps. This course teaches students the ways Python provides the power to gather data from the internet, regardless of the area of specialty, and to automate the information collected. Students will be able to write loops so the web scraping code can process large numbers of pages and stay relevant with up-to-the-minute information. No coding experience is necessary, although basic knowledge of HTML and CSS is highly recommended.

The Data Science Certificate prepares students for entry-level data science and Python engineering positions upon completion. The first section of this intensive program teaches the programming skills necessary to manipulate databases and perform various levels of analysis on data. The course then continues into specific requirements of the profession, using Python programming fundamentals and using Numpy, Pandas, and Matplotlib to analyze data. Students explore the three main data science libraries and how to create predictive models from the data using machine learning packages such as Sci-Kit Learn.

The Introduction to SQL Databases takes a hands-on approach to learning the basics through both labs and lectures. Expert instructors guide students through the fundamentals of data modeling, the use of relations databases, and the normalization of raw data. Attendees of this three-day class also learn how to design relationships, evaluate query performance, and use stored procedures.

In a fast-paced two-day dive into the essentials of how Python is incorporated in data analysis, the Using Data Science Tools in Python provides instruction with Python programming and works with NumPy Arrays, Pandas, and MatPlotLib to perform data analysis and create data visualizations.

Another two-day class designed for software developers, IT architects, and data scientists, the Python with Data Science course builds upon the students’ strengths in programming and teaches the theoretical and technical aspects for the uses of Python. This class follows the history and purpose of data science, along with the life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data, all through exercises in lab learning experiences.

Choosing a Data Science Bootcamp

There are a few different data science bootcamps to choose from, and each offers distinct differences and specific paths to follow. Noble Desktop, the creator of this tool, suggests reviewing some of the factors that help prospective students understand how to navigate their choices. With that in mind, using the Which Bootcamp is Right for Me page helps guide bootcamp candidates in the right direction. Students should feel confident in their decision, knowing they’ll receive the support and information they’ll need when beginning a new career path.

Bootcamps are the right choice for students dedicated to learning a solid amount of information over an extended, immersive, and hands-on session that prepares them for a career upon graduation. These classes have the advantage of 1-on-1 instruction and offer career coaching to help students lock down jobs in their preferred industry. Bootcamps provide a great way to establish relationships with other future data scientists, forming opportunities for friendship and professional networking that can last throughout a lifetime.

There is financing available for many of these bootcamps, as well. Some provide scholarship opportunities, while others offer the chance to pay in installments. All bootcamps provide career guidance and mentoring.

The application process for any bootcamp starts with prospective students exploring the different options offered to see which one feels right for them. Next, students determine which course is the best fit by examining course lengths, costs, coaching and mentorship opportunities, and the overall direction of data science that interests them. No matter which bootcamp they end up picking, they’ll be on their way to a lucrative, exciting career with the backing of the best data science bootcamps available.