How to Become a Data Scientist with LearningFuze

LearningFuze is meeting today’s demand for knowledgeable data professionals with their 25-week, part-time Data Science Bootcamp, led by a team of seasoned data professionals! Learn about which tech roles the Data Science Bootcamp prepares students for and the types of unique projects students will add to their portfolios. Plus, find out how to make the most of your bootcamp experience, whether you’re learning in person or online at LearningFuze!

👩🏾‍💻 Kick-start your data career and enroll in LearningFuze’s Data Science Prep course (a prerequisite for admission into the Data Science Bootcamp)! Applications close on April 7th, 2024.

Why is data science a good career path in 2024?

In 2024, data science remains a highly sought-after career path. The Bureau of Labor Statistics states that data scientist employment is projected to grow 35 percent between 2022 and 2032! Data is vital in the digital age, with a large number of sources generating vast amounts of information every second. This abundance of data presents myriad opportunities for data scientists to leverage their skills and extract valuable insights to drive informed decision-making. 

Across industries, organizations are increasingly recognizing the importance of data-driven approaches to gain a competitive edge, spurring a high demand for skilled professionals in the field. Data scientists play an instrumental role in helping companies leverage the power of data to identify trends, predict customer behavior, and innovate. This dynamic landscape creates high earning potential and provides flexibility and versatility, allowing data scientists to explore diverse career paths across industries, such as machine learning, artificial intelligence, and big data technologies. 

What can students expect to learn in the Data Science Bootcamp at LearningFuze? 

Our course is broken into two modules and covers Data Analytics, Machine Learning, and AI Systems:

• The first module covers fundamental Data Analytics topics, including data collection, exploration, visualization, preparation, and modeling for Machine Learning (ML). Students will get hands-on experience with WebScraping, APIs, SQL, Tableau, Python, and libraries such as Pandas and Matplotlib. In Module 1, students also start to explore supervised ML techniques including regression models and classification algorithms. 
• The second module focuses on advanced Data Science skills, including Machine Learning and AI Systems. In Module 2, students are taught Keras, TensorFlow, Neural Networks, Recommendation Systems, Image Recognition, Natural Language processing time series, Machine Learning in the Cloud, and more! 

In each class, students perform hands-on exercises that allow them to build a deeper understanding of foundational and advanced Data Science concepts. By the end of the course, students will complete six portfolio projects to gain real-world experience and stand out in the job market. 

Is the Data Science Bootcamp taught online and in person at LearningFuze?

Yes, because our class sizes are small (with a maximum of 10:1 student-to-instructor ratio), we can tailor the course to be taught online, in person, or in hybrid settings depending on the geographic location and needs of each cohort and students enrolled. 

How long does it take to complete the bootcamp? What kind of time commitment should students expect?

The course is 25 weeks or 6 months, consisting of two 12-week modules with a one-week break in between, and includes ongoing career support post-program. Live classes are held Monday through Thursday from 6:00pm - 9:00pm Pacific Standard Time. 

Students can expect 12 hours of weekly live classroom time, with a total of 20 hours of time investment per week to solidify their learning with hands-on assigned exercises, projects, reviewing course material, and additional guided self-study. Throughout the course, students have access to community support via Slack and a data coach who can help answer questions outside of class hours. 

Can students complete the bootcamp while working a job or balancing other commitments?

Yes, our part-time programs are designed for students with existing careers or  obligations on top of learning. That said, the course requires focus, dedication, and a genuine desire to learn on top of those existing responsibilities.

What kinds of projects will students work on in the Data Science Bootcamp?

During the course, students will have the chance to work on six portfolio projects: 

• In Module 1, students will complete a Data Visualization project, a Regression project, and a Classification project. 
• In Module 2, students complete a Natural Language Processing (NLP) project and an Image Recognition project. At the end of the course, each student will develop and complete a custom capstone project using a variety of skills to maximize the impact of decision-making from selected data.

Across all six projects, our students gain a broad spectrum of experience handling data, ensuring they are well-equipped for the field. They have the opportunity to work independently on personally selected, custom-designed projects, collaborate in group Kaggle competitions, and engage with real-world data projects for small business clients!

How do these projects prepare students for what it’s like to actually work in data science?

Through the hands-on projects offered during the course, students engage in applied learning, gaining practical experience using data science concepts and techniques to address real-world problems. They practice working in data teams, as well as owning projects end-to-end. Each project targets specific areas of data science, from data visualization to regression, classification, natural language processing (NLP), and image recognition, enhancing skill development across a diverse range of tools and methodologies.

Additionally, completing multiple projects with different disciplines allows students to construct a diverse portfolio that showcases their proficiency and accomplishments and hones their problem-solving skills, which encourages critical thinking and creativity in formulating hypotheses, analyzing data, and making data-driven decisions. The final capstone project allows students to synthesize their learning and tackle complex problems independently to demonstrate their ability to deliver meaningful insights and solutions using data science techniques.

Who are the instructors for the Data Science Bootcamp? What is their background in data science?

Our instructional staff is comprised of four data professionals who are passionate about developing up-and-coming data scientists. The lead instructor for the program is Zia Khan, who has developed his instructional style over the last 6 years. Zia has 25+ years of commercial engineering, cloud architecture, and data science experience facilitated by his Computer Science degree. He’s currently working as a Data Scientist outside of teaching the course. Zia understands the importance of “hands on the keyboard” teaching, asking students to work through exercises and projects to gain well-ingrained skills.

Our Data Science Bootcamp is also supported by instructors Sam Van Gorden and Tim Horist, who are experts in their respective fields of statistical knowledge and data structures. Finally, our Senior Data Coach, Frank Fletcher, has worked as a Data Scientist and Instructor and is available to students for after-hours support.

The data field is constantly advancing, and our data instruction team meets weekly to discuss and adjust our proprietary curriculum. This allows our team to offer the most modern skills, tools, and projects used within this evolving industry. 

Is there an ideal student for the Data Science Bootcamp?

Anyone who is determined can be successful in the industry, however, the ideal data scientist is passionate about building, creating, and assembling. They also enjoy problem-solving and working with data, and are detail-oriented and a logical thinker.

Is the Data Science Bootcamp appropriate for data or tech beginners? Is there a prep course incoming students can take to prepare for the bootcamp?

Yes! Our Data Science Bootcamp is geared towards beginner and intermediate students. Students who come in with basic business proficiency, some background in math and statistics, and knowledge of any prior coding language will excel in the course.

Before officially enrolling in the course, all prospective students must attend our two-week Data Science Prep course. This course goes over the fundamentals of Python and statistics and gives a high-level overview of core data science topics to prepare students to excel in the bootcamp. 

Enroll in LearningFuze’s next Data Science Prep course beginning on April 8th, 2024! 

What kinds of tech roles does the Data Science Bootcamp prepare students for?

Most graduates meet the criteria for entry-level positions unless they have prior experience, which can qualify graduates for more mid-level roles. Typical job titles of Data Science bootcamp graduates are data analyst, entry-level data scientist, senior data analyst, business analyst, machine learning engineer, data engineer, or statistician.

In the tech industry, the opportunity for learning never stops! We offer upskill short courses that our alumni (and the general public) can take to expand their knowledge. These courses are designed to aid data professionals in leveling up to their next mid-level and senior-level roles. 

LearningFuze has been teaching data science for a while now — What kinds of jobs have LearningFuze Data Science graduates obtained?

Post-program, LearningFuze graduates have gotten jobs such as business support analysts, data scientists, and data engineers across small to enterprise-level companies.

What is your advice to incoming students on how to make the most of the Data Science Bootcamp?

• Embrace the hands-on learning opportunities presented by the diverse range of projects offered throughout the program. Each project is a chance to apply your knowledge, hone your skills, and build a robust portfolio that showcases your capabilities to potential employers. 
• Cultivate your problem-solving abilities by approaching challenges with curiosity, persistence, and a willingness to experiment. Remember, the field of data science is ever-evolving, so stay curious, keep learning, and remain adaptable to new technologies and methodologies. 
• Embrace the opportunity to curate your learning experience to match your career goals. Because we offer such small class sizes at LearningFuze, our instructors can get to know each student and help customize course exercises and projects such as tailoring these practice problems to the industry or path the student is hoping to pursue.
• Stay committed to your growth as a data scientist throughout the course and you'll be well-prepared to excel in the bootcamp and beyond.

Find out more and read LearningFuze reviews on Course Report. This article was produced by the Course Report team in partnership with LearningFuze.