The Data Analytics Bootcamp offered by Analytica Camp is a comprehensive program designed to provide students with the skills and knowledge needed to succeed in the field of data analytics. The curriculum covers a wide range of topics, including data visualization, statistical analysis, machine learning, and big data processing.
The payment policy is based on getting hired or getting a full refund model.
Throughout the program, students will work on up-to 15 hands-on projects to apply what they've learned and gain practical experience. These projects will cover real-world scenarios and help students to gain experience with tools such as Python, SQL, Excel, and PowerBI/Tableau.
During Data Analytics Professional, you will be supported and guided individually by mentors who are professional industry experts.
The Data Analytics Professional includes a career services component that will help students with their job search, resume building and interview skills. The aim is to provide students with the skills and knowledge needed to secure a job in data analytics.
In addition to the curriculum, hands-on projects, deadlines, mentor support, and career support, the Data Analytics Professional offered by Analytica Camp also includes community benefits.
Participants will have the opportunity to connect with other students and professionals in the field through virtual networking events and group discussions. This will allow them to share ideas and knowledge, collaborate on projects, and build a professional network.
Analytica Camp also offers continued support and resources after the program, allowing students to continue learning and growing as data professionals, and stay connected to the community of data practitioners, which also provides networking opportunities to the graduates.
The Data Analytics Professional is designed to be completed on a part-time basis, with class time typically taking place in the evenings or on weekends to accommodate students' work and personal schedules. Participants can expect to spend approximately 8-10 hours a week in the classroom, depending on the schedule and format of the program.
In addition to the class time, students should also expect to spend time outside of the classroom studying and working on projects. The approximate hours a student would expect to study would be around 20-25 hours, this includes time for working on projects, reviewing class materials, and preparing for assessments. It's important to note that the time required for studying and completing projects will vary depending on the individual student and their prior experience with data science.