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- Learn the data science hierarchy of needs.
- Understand why everyone is learning Python.
- Take a crash course in statistics.
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- Springboard
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- Data Science Foundations to Core Bootcamp
Data Science Foundations to Core Bootcamp
Quick Facts
| particular | details | ||||
|---|---|---|---|---|---|
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Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
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Learning efforts
20-25 Hours Per Week
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Course overview
Data Science Foundations to Core Bootcamp certification is a 7-month course in online mode. Over the course of 7 months, you will learn the core skills needed to succeed as a data scientist. This course is designed for beginners as well as experienced so that they can start their careers in this field of data science. Data Science Foundations to Core Bootcamp certification by Springboard has a comprehensive curriculum that will teach students about probability skills, python foundational, and statistics as well. Once you finish this course you will be able to explore more in terms of technical units like machine learning, data wrangling, and SQL & Databases.
By the end of the Data Science Foundations to Core Bootcamp certification course, you will learn about the concept of basic probability. This course also will be able to provide you with the technique to tackle real and complex business problems with the help of different data science tools. These scientific tools will help you to understand and visualise data.
The highlights
- Beginner-Friendly
- 100% Online
- Expert Mentors & Career Coach
- Graduate in 7 Months
Program offerings
- 1:1 expert mentorship
- 1:1 career coaching
- Job guarantee.
Course and certificate fees
Fees information
$ 9,900 $13,900
In this course, the provider offers a range of payment options. We can submit our application fee one time, monthly, or we can also pay the fee after we get a job. In Data Science Foundations to Core Bootcamp certification fees can be paid by a loan and in instalments.
Data Science Foundations to Core Bootcamp Fee
Name of the Course | Fee |
Data Science Foundations to Core Bootcamp | $13,900 |
certificate availability
Yes
certificate providing authority
Springboard
Who it is for
The Data Science Foundations to Core Bootcamp certification classes are ideal for candidates who want to become any of the following:
Eligibility criteria
Certification Qualifying Details
To get the certificate of the Data Science Foundations to Core Bootcamp, candidates must have to pass all the assignments. Also, the candidate has to prepare all the projects given to him/her in the course.
What you will learn
Knowledge of python
Upon successful completion of the Data Science Foundations to Core Bootcamp training, you will learn about using Python to solve various coding problems and start a new journey in the field of Data Science. Plus, Data Science Foundations to Core Bootcamp certification syllabus will also let you learn about the latest data science concepts and also other technical skills which you’ll need further in the core curriculum.
The syllabus
Foundations: Beginner to advanced Python
Introduction to Python I
- Gain familiarity with Python in the data science context and learn coding basics.
- Take Datacamp’s introduction to Python course
Data Visualizations Detour
- Learn maps, time-series, charts, and how graphics reveal data
- Grasp logarithms, color and shape, and pie charts
- Envision the future of data visualization
Introduction to Python II
- Get acquainted with Matplolib, Python dictionaries and Pandas
- Learn logic, control flow and filtering, and loops
Intermediate Python I
- Learn the differences between tuples, lists, and dictionaries
- Understand packages and modules and handling dates and times in Python
Intermediate Python II
- Learn to to write functions, including lambda expressions
- Understand variable scope in complex code
- Write elegant and readable code using list comprehensions
- Complete a case study to apply learned concepts
Statistics I
- Distinguish between descriptive and inferential statistics
- Understand populations and samples
- Explain probability theory and calculate the standard deviation of a dataset.
Statistics II
- Learn binomial and normal distributions, Hypothesis testing workflow, and independent and dependent variables
- Reinforce skills through DataCamp lessons.
What is Data Science?
- Learn about key data science skills
- Understand the six steps to the Data Science Method
Problem Identification
- Work through SMART problem statements
- Fill out problem statement worksheets
The Python Data Science Stack
- Follow best coding practices in Python
- Learn Python data types, foundations, and standard libraries
- Learn Pandas
Applying the Data Science Method
- Familiarize yourself with the six steps of the Data Science Method
- Learn problem identification, data wrangling, exploratory data analysis, pre-processing and training data development, modeling, and documentation
- Complete a guided capstone encapsulating steps in the DSM and presenting findings to executives
Data Wrangling
- Submit ideas and a project proposal for your second capstone
- Review data types, build data profiles, and develop and understand your data's features
- Wrangle data for your second capstone
SQL and Databases
- Learn the landscape of SQL and databases
- Write queries in SQL
- Work with relational databases in Python
Statistics for Exploratory Data Analysis
- Become equipped with essential conceptual knowledge before diving into application statistics
- Assess uncertainty through resampling
- Learn probability theory and hypothesis testing
- Delve into advanced statistics
Python Statistics in EDA
- Transfer statistical concepts into practical skills and learn how to implement statistical concepts in Python
- Take a deep dive into statistical inference, hypothesis testing, and statistical modeling in Python
- Incorporate learning from data visualization in Python
Machine Learning Overview
- Explore the fundamentals of machine learning
- Gain an understanding of the taxonomy of different types of ML algorithms
- Develop an understanding of best practices and common challenges that data scientists deal with when working on machine learning applications
Supervised Learning
- Develop an understanding of supervised learning and its common applications
- Be able to perform regression and classification techniques to solve real-world problems
Unsupervised Learning
- Develop knowledge of common clustering types
- Be able to perform clustering techniques to solve real-world problems
- Complete a distance metrics exercise and a cosine similarity exercise
Feature Engineering
- Perform data transformation for categorical features, image features, and text features
- Learn best practices for deriving features, handling missing data, and automated feature engineering
- Apply feature engineering techniques to step four of your second capstone: pre-processing and training data development
Machine Learning Applications
- Take a deep dive into the types of evaluation metrics for regression and classification
- Be able to choose the best evaluation metric for your machine learning project
- Learn best practices for model optimization
Data Storytelling
- Learn how to apply presentation techniques for executive (C-suite), technical, and non-technical audiences
- Prepare a presentation about a dataset of your choosing
- Finalize the documentation of your second capstone project
- Give a presentation about the work you completed for your second capstone
Specialization Tracks
- Option 1 — Generalist Track:
- Option 2 — Business Insider Tracker:
- Option 3 — Advanced Machine Learning:
Projects
Career Support
- Types of industry roles
- Job search strategies
- Building a network and using it to land interviews
- Creating a high-quality resume, LinkedIn profile, and cover letter
- Preparing for technical and non-technical interviews
- Successful negotiation
Admission details
To apply for the Data Science Foundations to Core Bootcamp online course you will have to follow these instructions:
Step 1: Login to www.springboard.com
Step 2: Then click on courses > Foundation to core data science or click directly on https://www.springboard.com/courses/foundations-to-core-data-science/#job-guarantee.
Step 3: Click on the “Apply Now” button.
Step 4: Add your email address and then press Enter.
Step 5: Fill in your details and you are good to go.
Filling the form
The candidate has to add his/her first name, last name, and phone number to the application form. After that, the candidate has to select his current location followed by a preferred start date for the course. Then the candidate has to answer some more questions and in the end, he has to upload his/her resume on the portal.
Scholarship Details
Yes, candidates can apply for the provider scholarship via the main application of this Data Science Foundations to Core Bootcamp Certification Course. To apply for the scholarship candidate must have to effectuate his/her eligibility for the scholarship by answering some additional questions.
- Provider offers scholarship to:
- Refugees
- Anyone without the means to afford a Bootcamp
- LGBTQ+ individuals
- People of colour
- Veterans
- Women
How it helps
Data Science Foundations to Core Bootcamp certification benefits the students by providing them with vast knowledge of data science and how they can learn the skills needed to establish their career in the field of data science. The certificate also provides you with a job guarantee within 6 months of graduating.
FAQs
What is included in Data Science Foundations to Core Bootcamp online course?
The course includes basic to advanced Python, regular 1-1 video calls with your mentor, doubt-solving, and lots of interview practices.
Will I earn a Data Science Foundations to Core Bootcamp online certification?
Yes, once you complete the course and all the projects and assignments, you will receive a signed certificate of completion from the provider.
What kind of support can I expect in this course?
You will get support from your mentor, teaching assistants, your carrier coach, and student advisor.
Is Data Science a promising career?
Data science is a great career with a lot of demand and future growth.
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