{"id":91086,"date":"2021-10-21T18:32:50","date_gmt":"2021-10-22T01:32:50","guid":{"rendered":"https:\/\/careerkarma.com\/blog\/?p=91086"},"modified":"2021-10-21T20:34:43","modified_gmt":"2021-10-22T03:34:43","slug":"learningfuze-data-science-bootcamp-review","status":"publish","type":"post","link":"https:\/\/careerkarma.com\/blog\/learningfuze-data-science-bootcamp-review\/","title":{"rendered":"How LearningFuze\u2019s Data Science Courses Can Be a Fastlane to a New Career"},"content":{"rendered":"\n

The data science field is booming, with corporations looking to harness the 79 zettabytes of data <\/a>that have ever been and will ever be created, captured, copied, and consumed. To put a zettabyte into perspective, it\u2019s about 909,494,702 terabytes, and most of that data was created in the past five or so years.<\/p>\n\n\n\n

Companies use data to peer into the thoughts, habits, and desires of their customers to develop better products. And the responsibility of interpreting that data in a way companies can use falls onto the shoulders of their data teams.<\/p>\n\n\n\n

Data teams usually contain three roles: data analysts, data engineers, and data scientists. Most tech bootcamps offer courses in data analytics and data science, with the understanding that you\u2019ll spend a few years as a data analyst to learn the ropes before coming back to learn the intricacies of the subject. <\/p>\n\n\n\n

But LearningFuze<\/a> has taken a different path. Due to an overwhelming amount of requests from the bootcamp\u2019s hiring partners, it’s been able to add a unique element to its data science course: an unusually rapid start to a data science career.<\/p>\n\n\n\n

\n

LearningFuze students gain lifelong access to the curriculum and career services, setting them up for a sustainable and successful tech career.<\/p>\nAttend Learning Fuze\u2019s Info Session today.<\/a>\n<\/div>\n
\n\n\n\n

Why Learn Data Science?<\/strong><\/h2>\n\n\n\n

Data science is one of the fastest-growing job markets on the planet, ranking third in LinkedIn\u2019s 2020 Emerging Jobs Report<\/a>. Data scientists are in high demand, and their salaries reflect that, with entry-level jobs paying about $85,312<\/a> per year, according to PayScale. These statistics show that this field has a unique combination of high salaries and open opportunities that make it a great career choice. <\/p>\n\n\n\n

What Is Data Science?<\/strong><\/h3>\n\n\n\n

Data science is a discipline involving the use of data generated by a company to reach several conclusions for better decision-making.<\/p>\n\n\n\n

Many data scientists begin their careers as data analysts. These professionals pull preexisting data from an organized data warehouse and present logical conclusions to answer specific questions. They then present their visualized findings to company stakeholders.<\/p>\n\n\n\n

Data analysts tend to evolve into one of the two other roles: data scientists or data engineers. Data scientists go one step further than analysts, using machine learning and artificial intelligence to help companies forecast events based on past data. Meanwhile, data engineers build automated pipelines that take raw unsorted data from data lakes and place them into data warehouses, where sorted information is easier to find. <\/p>\n\n\n\n

One reason why most people start as data analysts is that the field is very new. Many organizations are still figuring out the nuances of assembling a data team. Because of this, they\u2019re simply going off of what they\u2019ve heard about what makes a good data scientist instead of knowing what their company truly needs.<\/p>\n\n\n\n

But as LearningFuze\u2019s vast network of hiring partners has shown, companies are willing to hire fresh data scientists as long as they\u2019ve proven to be competent. This school provides the correct learning structure and partnerships to let you skip the obligatory time in data analytics and get right to the role you\u2019ve dreamed of playing in data.<\/p>\n\n\n\n

LearningFuze Data Science Courses: Here\u2019s What to Expect<\/strong><\/h2>\n\n\n\n

LearningFuze offers two courses to help you transition into data science; the Data Science Prep Course<\/a> gives you an accessible entry-point to the field, while the part-time Data Science Bootcamp<\/a> builds on your skills to help you start a new career.<\/p>\n\n\n\n

The Data Science Bootcamp offers both in-person and remote options so you can access LearningFuze\u2019s future-proofed curriculum from anywhere. This course covers many topics you\u2019ll need to make your mark as a data scientist, like machine learning and artificial intelligence. <\/p>\n\n\n\n

But before you tackle the full course\u2019s challenging curriculum, you\u2019ll begin with the school\u2019s entry-level course.<\/p>\n\n\n\n

Data Science Prep Course<\/strong><\/h3>\n\n\n\n

LearningFuze\u2019s Data Science Prep Course gives students the foundation in the Python programming language, statistics, and data science before starting the Data Science Bootcamp. This part-time course introduces these topics and more during its two-week span. <\/p>\n\n\n\n

Though the course costs $245, it\u2019s free to anyone who attends a Data Science Info Session<\/a> at LearningFuze.<\/p>\n\n\n\n

Students also learn about working with Github for version control and complete their projects to start applying the knowledge they\u2019ve earned in the course. All you need is a computer that meets the program\u2019s system requirements<\/a>, basic computer knowledge, and to be at least 18 years of age.<\/p>\n\n\n\n

The course takes place over six sessions over two weeks. You\u2019ll study for two Saturdays from 10 am to 2.30 pm PST, and two Mondays and Wednesdays from 7 pm to 9 pm PST. Each session is recorded for easy viewing later, and the sessions include over 25 lessons and exercises with real-world projects and skill assessments. <\/p>\n\n\n\n

You\u2019ll have to commit 10 hours per week to the program, whether you choose the in-person or remote options. The next available prep course is scheduled for October 4 to October 16.<\/p>\n\n\n\n

The prep course is required for people who want to attend the full bootcamp. You\u2019ll learn the basics of core concepts that you\u2019ll carry throughout your career, like Python and statistics, and how to work with others in a collaborative environment. After completing this course, you\u2019ll be ready to advance to the next level.<\/p>\n\n\n\n

Data Science Bootcamp<\/strong><\/h3>\n\n\n\n

The Data Science Bootcamp builds on the foundations that you\u2019ve laid in the prep course to get you ready for a new career. This course is split into two modules. In the first module, you\u2019ll strengthen your machine learning knowledge. After you\u2019ve grasped the powers of machine learning and its associated skills, you\u2019ll advance to the second module: Deep Learning and Artificial Intelligence.<\/p>\n\n\n\n

Module One: Machine Learning<\/strong><\/h4>\n\n\n\n

The first module is for anyone who needs an introduction to data science principles. You\u2019ll learn more about Python, along with its libraries like Pandas and Matplotlib. You\u2019ll also add SQL knowledge to help you navigate the databases of many potential employers. <\/p>\n\n\n\n

Along with the instruction on machine learning, you\u2019ll also learn about web scraping, data cleaning, and statistical analysis. These tools have several benefits, and in the first module, you\u2019ll start to see how these tools assist with the different data science career paths. <\/p>\n\n\n\n

Web scraping allows you to quickly extract data from multiple websites using machine learning tools. Data cleaning is the process of identifying corrupt, outdated, and inaccurate data in a collection and replacing it with useful data. Through the power of statistical analysis, you can gather giant swaths of data and look for patterns to give your employer an idea of what to expect in the future. <\/p>\n\n\n\n

Module Two: Deep Learning and Artificial Intelligence<\/strong><\/h4>\n\n\n\n

The second module is a deeper dive into data science for people with more experience. After this module, you\u2019ll walk away with a firmer understanding of deep learning and artificial intelligence tools and concepts.<\/p>\n\n\n\n

These tools and concepts include natural language processing, image recognition, machine learning in the cloud, and neural networks. Natural language processing and image recognition are two fundamental deep learning processes. “Natural language processing” refers to how machines can efficiently read and understand human language, while image processing is a similar process revolving around quickly recognizing and categorizing images.<\/p>\n\n\n\n

Cloud-based solutions like AWS and Docker provide data scientists with the ability to scale storage quickly while also running applications to clean and categorize that same data. Neural networks are machines that work similarly to the human brain by quickly recognizing patterns and categorizing information. Many neural networks are also capable of learning on their own to streamline their work. <\/p>\n\n\n\n

To assist your work, you\u2019ll pick up new tech like Kera and Tensorflow, among others. <\/p>\n\n\n\n

Regardless of if you decide to take the in-person or the remote course, you\u2019ll be in class from 6 pm to 9.30pm PST on Monday, Tuesday, and Thursday. Your instructors will also offer office hours on Wednesday from 2pm to 9.30pm, and on Monday, Tuesday, and Thursday from 2pm to 6pm. The next course is scheduled for October 18 to January 14.<\/p>\n\n\n\n

After completing this course, LearningFuze believes you\u2019ll be prepared for a career in data science with one of its many hiring partners. <\/p>\n\n\n\n

Course Benefits<\/h4>\n\n\n\n

This course is the direct result of LearningFuze\u2019s 300+ hiring partners asking them to implement a high-quality program. Because these hiring partners believe so strongly in the strength of the bootcamp\u2019s work, they\u2019ve reportedly been quick to hire LearningFuze\u2019s students. Much of the bootcamp\u2019s quality lies in its low teacher-to-student ratio and its industry-ready curriculum.<\/p>\n\n\n\n

This course, much like LearningFuze\u2019s Software Development Coding Bootcamps<\/a>, has a low teacher-to-student ratio of about 6:1. LearningFuze likes to keep this ratio intact, as the bootcamp believes that students deserve attentive instructors that can help them on a more personal level. <\/p>\n\n\n\n

The course\u2019s industry-ready design is courtesy of Senior Instructor Zia Khan<\/a>, a data scientist with over 20 years of experience in the field. Zia has been teaching at the program for over four years and holds numerous certifications from the likes of Cisco, EMC, Salesforce, and Python. With his industry knowledge and instructional experience, he\u2019s worked to ensure that the course gives every student what they need to take the next step. <\/p>\n\n\n\n

Besides these other benefits, the course also includes an accessible price. <\/p>\n\n\n\n

Payment Options <\/strong><\/h3>\n\n\n\n

Both modules cost $5,995 each for a total cost of $11,990, with early registration discounts of $250 for each course. You can lower the price with multiple payment options<\/a>.<\/p>\n\n\n\n

There are also $250 discounts for women and veterans who attend the program and a $500 discount for paying upfront. You can also choose to pay for your studies with a loan from LearningFuze\u2019s partner Ascent. Ascent offers interest-only and deferred payment options, both with no money down. <\/p>\n\n\n\n

In the interest-only option, you\u2019ll only pay interest for six months after the program starts. In the deferred option, you\u2019ll pay nothing for six months after the start of the program.<\/p>\n\n\n\n

Is Data Science Right for Me?<\/strong><\/h2>\n\n\n\n

If you enjoy coding, working with statistics, and putting together a story from information, then it certainly can be. Data science is a field that has far-reaching applications across many different industries, from finance to tech and even science.<\/p>\n\n\n\n

If you\u2019re trying to decide whether you\u2019d prefer to start your new tech career in software engineering or data science, both options provide plenty of opportunities. Software engineering, as the discipline concerning building and maintaining desktop and web apps, is more for people who prefer coding alone.<\/p>\n\n\n\n

You can certainly start your own business as a software engineer, but presentation skills and business acumen aren\u2019t especially necessary to find your first job. In data science, you\u2019ll have to communicate with internal and external stakeholders often. You\u2019ll also be using machine learning and the other tools mentioned above to create projections of a company\u2019s future performance based on existing data.<\/p>\n\n\n\n

Of course, because every company uses its data differently, you\u2019ll need a wide range of experience while learning the craft. One LearningFuze data science student told Career Karma that she felt the program gave her everything she needed to make the right decision. <\/p>\n\n\n\n

LearningFuze Data Science Student Review<\/strong><\/h2>\n\n\n\n

Belle Shen worked as a project manager for five years before attending the Data Science Bootcamp. But before she worked in that position for a manufacturing company, she was obtaining her master\u2019s degree in astronomy after a bachelor\u2019s degree in physics.<\/p>\n\n\n\n

\u201cA lot of people think that astronomers look up at the skies to see the stars every night, but in reality, we basically collect data,\u201d Belle said. \u201cWe analyze the data, use mathematical functions, and we also need to code.\u201d<\/p>\n\n\n\n

During her time as a project manager, she performed some light data analysis to find patterns in datasets, and she found herself drawn to it. She did her own research and chose LearningFuze due to its prep course, and her trust in Senior Instructor Zia Khan. <\/p>\n\n\n\n

\u201cBecause I come from a physics background, if I don\u2019t know how to describe my problems, I\u2019ll kind of use the math or physics way to explain my question,\u201d Belle said. \u201cZia came from a similar background as me, so even if I couldn\u2019t describe my question very well, I knew he\u2019d understand what I was talking about.\u201d <\/p>\n\n\n\n

Though she did have minimal data analytics experience, she decided to pursue data science through LearningFuze\u2019s program because of her love for machine learning. As a bonus, Belle found that LearningFuze\u2019s staff was kind and very helpful. The helpful staff and skillful instructor gave Belle such a positive experience, it was hard for her to decide her favorite part of the course.<\/p>\n\n\n\n

\u201cI think I enjoyed every topic,\u201d Belle said. \u201cI enjoyed learning, and I also enjoyed our projects because I never did data analysis on this level before. We analyzed loan data sets for the banking and financial industry. And we\u2019ve also analyzed the real estate data, like, house prices. Because my previous job was all manufacturing, I never had a chance to touch that part, but so far it\u2019s quite fun.\u201d<\/p>\n\n\n\n

Because there\u2019s so much variety in the data science field, Zia Khan gives students plenty of opportunities to find which field appeals to them most. <\/p>\n\n\n\n

\u201cZia wants us to try every industry\u2019s data so that we can choose which industry we\u2019re more interested in and start our career there,\u201d Belle said. \u201cI really liked this structure.\u201d<\/p>\n\n\n\n

As an example of the field\u2019s versatility, her data science studies have allowed Belle to get back into her passion for astronomy. After graduation, she feels like she can finally fulfill her childhood dreams. <\/p>\n\n\n\n

\u201cI think it\u2019s because of my background in astronomy and astrophysics, but I want to work in the aerospace engineering industry, space exploration, or defense,\u201d Belle said. \u201cIt\u2019s kind of my passion. I made the decision to be an astronomer when I was 10.”<\/p>\n\n\n\n

Belle has some advice for anyone that\u2019s considering data science as the path to a more fulfilling career. <\/p>\n\n\n\n

\u201cI think you have to be open-minded no matter what,\u201d Belle said. \u201cAll of us students came from different backgrounds, so I can say that even if you don’t have any coding experience, you can just trust Zia. He’s very patient and he\u2019ll explain everything to you in great detail. So if you don’t understand, just keep asking. He\u2019ll answer anything. And if you\u2019re just tired or exhausted from the projects and exercises, be sure to take breaks.\u201d<\/p>\n\n\n\n

If you\u2019re interested in learning more about this Data Science Bootcamp, be sure to attend LearningFuze\u2019s next available Info Session<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"The data science field is booming, with corporations looking to harness the 79 zettabytes of data that have ever been and will ever be created, captured, copied, and consumed. To put a zettabyte into perspective, it\u2019s about 909,494,702 terabytes, and most of that data was created in the past five or so years. 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