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Data Analytics & Visualization Bootcamp
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Learning efforts
30 Hours Per Week
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Course overview
The Data Analytics & Visualization Bootcamp certification course is provided through the platform named Coding Dojo. The programme is ideal for students who want to learn about data science and machine learning. Candidates who get into the programme learn about the subject matter through four different chapters. The Data Analytics & Visualization Bootcamp certification syllabus requires 12 weeks of time duration to be completed by a student if he or she spends a minimum of 20 hours per week. The self-paced Data Analytics & Visualization Bootcamp classes enable students to pursue the course according to their own time table. Students who are beginners in this field can also apply for the Data Analytics & Visualization Bootcamp online course along with the professional candidates. The Data Analytics & Visualization Bootcamp online certification deals with the basics as well as an advanced level of topics in the programme.
The highlights
- Part-time course
- 16 weeks programme
- Online mode of learning
- 30 hours per week
- Beginners, as well as professionals, can apply
- Career services available
- Self paced course
- Certification can be obtained
Program offerings
- Video sessions
- Projects
- Modules
Course and certificate fees
certificate availability
No
Who it is for
The Data Analytics & Visualization Bootcamp certification is intended for the following people-
Candidates who want to pursue this course professionally.
Eligibility criteria
Certification Qualifying Details
Once the student completes the programme entirely, he/she becomes eligible for the certification of completion.
What you will learn
Machine learning
Data science knowledge
Participants can obtain the following learnings through the Data Analytics & Visualization Bootcamp programme-
- Candidates will learn about the fundamentals of Python.
- Students will gain insights into manipulation and understanding of data in the Data Analytics & Visualization Bootcamp training.
- Participants will come to know about the weaknesses as well as strengths of using Python in the manipulation of data.
- Candidates will learn about data modeling.
- Candidates will get to know the fundamentals of machine learning.
- Students will learn the statistics used in Python in the Data Analytics & Visualization Bootcamp certification.
The syllabus
Precourse Work
Python Basics Pre-coursework
Weeks 1 to 4
Data Science Fundamentals
- Python Fundamentals
- Load, explore, and understand data in Pandas
- Exploratory Data Analysis (EDA) using Seaborn & matplotlib
- Create and customize plots for explanatory visualizations
Weeks 5 to 8
Intro to Machine Learning
- Formatting and preprocessing for supervised Machine Learning
- Train models in regression, classification, and supervised learning
- Model Optimization
- Extract, visualize, and interpret model insights
Weeks 9 to 12
Data Enrichment
- Database architecture in SQL
- Intro to ETL: navigate JSON files, extract from APIs, and convert Panda dataframes
- Hypothesis testing, interpretation of results, and communicating results to stakeholders in non-technical terms
- Advance SQL
Weeks 13 to 16
Data Visualization
- Time Series Analysis in Python
- Applying Machine Learning to forecast Time Series data for both short and long term
- Perform analysis and quality visualizations in Tableau
- Create interactive, responsive dashboards within Tableau
Admission details
Students can follow the given guidelines for the admission process of the Data Analytics & Visualization Bootcamp programme-
Step 1- Candidates need to apply for the course from the webpage of the course.
Step 2- Candidates need to select the Apply Today option.
Step 3- Candidates must fill the required admission form.
Step 4- Candidates need to make the payment after the submission.
How it helps
The Data Analytics & Visualization Bootcamp online course is a self paced course that can be pursued according to the comfort of the students. The course is a part time course and thus requires a shorter amount of time to complete the course and can be finished if the student spends at least 20 hours a week of time for 12 weeks. Upon completing the Data Analytics & Visualization Bootcamp programme successfully, students get the certification that impacts the professional growth of the candidate in a positive way.
The Data Analytics & Visualization Bootcamp certification benefits include applying to jobs and internships by the students. Candidates can apply for a higher degree in the program if they want after pursuing the course. The candidate will be able to get a job due to the interview practice taught to him/her in the certification. The achievement of the certification boosts the weightage of the job profile of the candidates.
FAQs
How can I apply for an online Data Science part time bootcamp course?
The candidate can get admitted into the programme by filling the application followed by submission of the Data Analytics & Visualization Bootcamp fee.
Will I be placed by the platform after completing the Data Analytics & Visualization Bootcamp online training?
No, the platform does not offer placement options.
How can I obtain the certification?
The certification can be obtained only by completing the entire Data Analytics & Visualization Bootcamp online course.
Is it possible to make the payment in instalments?
Yes, the Data Analytics & Visualization Bootcamp certification course gives the option to students to make the payments in instalments.
When can I start the programme?
Students can start the programme as soon as they join the sessions.
Do I need to have work experience to apply for the course?
Students who don't have any work experience can also apply for the Data Analytics & Visualization Bootcamp by Coding Dojo.
How will I be able to complete the syllabus on time?
If the student devotes 30 hours a week to learn from the course, he/she can complete the syllabus on time.
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