The Data Science Bootcamp is an intensive, part-time evening program designed to prepare highly motivated adult learners with prior experience in statistical reasoning, quantitative research, and/or software engineering for a job as a Data Scientist, Analytics Consultant, Data Engineer or related position.
Data Science lies at the intersection of statistics/quantitative analysis, business acumen/domain expertise, and programming/“hacking” skills. The bootcamp focuses on hands-on training in software engineering skills required to do data science as well as applying the necessary stats/math/analytical skills against real world problems drawn from a wide range of problem domains.
We believe that the MAKENOW has an untapped supply of latent talent for data analytical work. But, that talent needs access to accelerated, focused, real-world training. We’ve designed the Data Science Bootcamp to help address this need.
Python & R
You will learn to create data analytic workflows in the two most widely used programming languages in data science. You will learn the editors, IDEs, source code control systems, etc. used by Data Scientists.
Data Science Toolkit
You will gain facility in using the most popular libraries and packages associated with Python and R, e.g. pandas, scikit-learn, the tidyverse. You’ll learn to use RStudio and Jupyter Notebooks for writing code and documenting workflow.
Data Science Process
You’ll learn the project life-cycle of a typical data science project. You’ll learn how to identify the business question, how to create and refine your hypothesis, build models, test and iterate the analysis, and ultimately deploy the resulting data product and communicate the results.
Managing & Curating Data
You’ll learn the process of collecting, extracting, querying, cleaning, and aggregating data for analysis. You will apply the tools in both the Python and R toolkits to this process in multiple projects. You’ll spend time wrangling data, understanding data quality issues, and learning how to clean data. You will work with a variety of data sources from unstructured/semi-structured text files to delimited/structured file formats such excel, csv, json, xml etc. You’ll also learn about web scraping and working with APIs.
Exploring Data Analysis
You will learn exploratory techniques for visualizing & summarizing data. These techniques are typically applied before formal modeling. Exploratory techniques are important for eliminating or sharpening potential hypotheses as well as identifying problems with the data that need to be addressed before modeling. We will cover plotting libraries (matplotlib, seaborn, ggplot2, etc.) as well as some of the basic principles of constructing data visualizations.
SQL,Data Management & Big Data
You’ll master the use of SQL to query relational databases. You’ll also be introduced to the 4 main types of NoSQL systems and understand the tradeoffs of using each one.
You’ll be introduced to techniques for working with Big Data in a cloud environment.
Machine Learning : Supervised
You’ll learn to use training data to develop supervised machine learning models and apply them to a range of different problems. Some of the concepts you’ll learn about include:
Machine Learning : Unsupervised
You’ll learn to apply unsupervised machine learning algorithms to uncover trends and patterns in data. You'll get familiar with:
Natural Language Processing
You will learn to extract meaning from text by applying techniques such as:
Data Visualization & Comunication
A key skill for data scientists is presenting the results of their projects to business decision makers and other stakeholders. You’ll learn common tools and techniques of data visualization and how to use them for effectively communicating the story of your data and your analysis.
Real World Projects
You will be able to apply the skills you are learning to real-world datasets and problems from various domains, such as healthcare, financial services, entertainment, consumer marketing/retail, and government. Projects will be executed primarily in a team environment so you’ll get experience working with others in a multi-disciplinary project team.
Your capstone project will be an individual effort that demonstrates your ability to take a data science project through the entire data science process. This project will demonstrate to potential employers your ability to apply the skills learned in this class to a real-world problem and present your findings.
Throughout the bootcamp you will also be preparing to move into a data science job. You’ll meet working data scientists from several industries. We’ll hold workshops on resume preparation/marketing yourself, interview preparation, negotiating, and more. And we’ll introduce you to prospective employers at your class Demo Day and support you after graduation during your job search.
Tuesday, Thursday :- 6PM - 9:30PM
Saturday :- 9AM - 2PM
The class is remote
September 14,2021 - June 16,2021
Student prerequisite knowledge/experience
Thanks to DataCamp for partnering with us through their Education program to support learning in our data science bootcamp. DataCamp is an interactive learning platform for data science. Their partnership provides our Data Science students access to their content in R, Python, and SQL on importing data, data visualization, machine learning, deep learning & more.
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