Data Science Bootcamp
Learn data science with Approved America’s award winning curriculum and top notch instructors. Data Analyst Instructor : Rhonda Coleman Albazie and 12 Additional, Data Science Instructors
20 Hours of Study per Week
Starting at $6,500
24 Weeks
- Over 500 hours of data science study content, jammed packed with data science fundamentals, data trends, relational database management systems (RDBMS), cloud databases, python programming, SQL, Ipython, and hands on experience with data science tools including JupyterLad, R Studio, GitHub and Watson Studio plus write SQL statements and query Cloud databases using Python from Jupyter notebooks.
- Our most affordable data science boot camp offering payment plans and flexibility options
- Approved America offers Data Science in three tiers of data-rich training featuring fast track career education + training + internship options. Get approved.
Module 1: Introduction to Data Science Fundamentals
Interested in starting a new career in data science? Get approved. Approved America Data Science course delivers the key foundational skills to develop command mastery of data science for entry level and advanced careers as a data scientist. You’ll discover what data science is, what data scientists do, which tools data scientists use and how to leverage data to make strategic data driven decisions to best serve invested stakeholders.
Week 1: Welcome To Approved America Data Science with Course Primer
- What Data Science Is, Why Data Science Is Important and What Data Scientists Do
- Approved America’s ‘hands-on’ Jupyter activities
- Approved America’s Python Primer
- Data Science Glossary of Terms
- Approved America Bibliophile’s Data Science Reading List
- Approved America Data Scientist Interlocked Networks
Week 2: Introduction to Data Science Core Concepts, Technologies and Trends
- The Data Science Process
- Approved America’s Data Science ToolKit
- Types of Data and Applications Plus Examples
Week 3: Data Collection and Data Management
- Sources of Data
- Data Collection and APIs
- Exploring and Fixing Data
- Data Storage and Management
- Using Multiple Data Sources
Week 4: Data Analysis
- Introduction to Statistics
- Basic Machine-Learning Algorithms
Week 5: Data visualisation
- Types of Data Visualization
- Data for Visualization
- Technologies for Visualization
Week 6: The Future of Data Science Plus Data Trends
- A Comprehensive Overview and Exploration of the Future of Data Science
No previous data science or computer programming experience required.
Get approved and start today.
Approved America Technology Training Data Science Certificate Upon Completion.
Additional Advanced Data Analytics Certificates Available For Approved America Alumni.
Offering interlocked networking internships and job placement for graduates.
Path
1.1 What Data Science Is and Why It’s Important
1.2 Hands-on Jupyter Primer Activities
1.3 Approved America Python Primer
Module 2: Mathematical and Statistical Skills
The Approved America Data Science Mathematical and Statistical Module covers
- Introduction to Statistics
- Terminologies in Statistics
- Categories in Statistics
- Understanding Descriptive Analysis
- Descriptive Statistics in R
- Understanding Inferential Analysis
- Inferential Statistics in R
Path
1.1 Introduction to Statistics
1.2 Terminologies In Statistics
1.3 Categories In Statistics
Module 3: Machine Learning
Gain command mastery of supervised and unsupervised machine learning.
Intro to Supervised/Unsupervised Learning
- Decision Trees
- Linear Regression: OLS, Regularization, Linear Classifiers
- Logistic Regression, Multi-Class Logistic Regression Ranking Support Vector Machines
- Feature Selection Latent Factor Models (PCA)
- Clustering (k-means, soft k-means)
- Ensemble Methods such as Random Forest and Ada Boost
- Probabilistic methods (Bayesian view)
- Model evaluation and model selection
- Introduction to Neural Networks and Convolutional Neural Networks
- Autoencoders
Path
1.1 Supervised and Unsupervised Learning
1.2 Decision Trees
1.3 Linear Regression : OLS, Regularizatin and Linear Classifiers
Learn Path
Career Resources
The Approved America Data Science curriculum includes :
- Introduction to Data Science
- Mathematical & Statistical Skills
- Machine Learning
- Coding
- Algorithms used in Machine Learning
- Statistical Foundations for Data Science
- Data Structures & Algorithms
- Scientific Computing
- Optimization Techniques
- Data Visualization
- Matrix Computations
- Scholastic Models
- Experimentation, Evaluation and Project Deployment Tools
- Predictive Analytics and Segmentation using Clustering
- Applied Mathematics and Informatics
- Exploratory Data Analysis
- Business Acumen & Artificial Intelligence
Curriculum
Module1
Introduction To Data Science Fundamentals
Module2
Mathematical and Statistical Skills
Module3
Machine Learning
Module4
Coding
Module5
Algorithms Used In Machine Learning
Title
Statistical Foundations for Data Science
Title
Data Structures and Algorithms
Title
Scientific Computing
Title
Optimization Techniques
Title
Data Visualization
Title
Matrix Computations
Title
Scholastic Models
Title
Experimentation, Evaluation and Project Deployment Tools
Title
Predictive Analytics and Segmentation Using Clustering
Title
Applied Mathematics and Informatics
Title
Exploratory Data Analysis
Title
Business Acumen & Artificial Intelligence
Module 4: Coding
Learn coding skills, the secrets of writing well tested simple to improve programs to develop command mastery of programming languages and advance your career as a data scientist.
The Approved America Data Science Coding Module will cover :
- How to represent information as data
- How to focus each part of your program on a single task
- How to use examples and tests to clarify what your program should do
- How to simplify the structure of your program using common patterns
- Recognize and represent more complicated information
- R Programming
- Python Primer
- Hadoop Platform
- SQL Database/Coding
- Java
- Perl
- C/C++
- Analyze Data With Python
- Apache Spark
- Machine Learning and AI
- Data Visualization
- Unstructured Data
Path
1.1 How To Represent Information As Data
1.2 Python
1.3 Analyze Data with Python
Module 5: Algorithms Used In Machine Learning
Introduction to Algorithms Used In Machine Learning
Algorithm Descriptions – A comprehensive overview of the linear, nonlinear and ensemble algorithm descriptions:
- Algorithm 1: Gradient Descent.
- Algorithm 2: Linear Regression.
- Algorithm 3: Logistic Regression.
- Algorithm 4: Linear Discriminant Analysis.
- Algorithm 5: Classification and Regression Trees.
- Algorithm 6: Naive Bayes.
- Algorithm 7: K-Nearest Neighbors.
- Algorithm 8: Learning Vector Quantization.
- Algorithm 9: Support Vector Machines.
- Algorithm 10: Bagged Decision Trees and Random Forest.
- Algorithm 11: Boosting and AdaBoost.
- How To Talk About Data In Machine Learning
- Algorithms Learning Mapping From Input to Output
- Parametric and Non-Parametric Algorithms In Machine Learning
- Supervised, Unsupervised and Semi-Supervised Learning
- The Bias Variance Trade-Off
- Overfitting and Underfitting
- Crash Course In Spread Sheet Math
- Gradient Descent For Spread Sheet Math
- Linear Regression
- Simple Linear Regression Tutorial
- Linear Regression Tutorial Using Gradient Descent
- Logistic Regression
- Logistic Regression Tutorial
- Linear Discriminant Analysis
- Linear Discriminant Analysis Tutorial
Non-Linear Algorithms
- Classification and Regression Trees
- Classification Trees and Regression Tutorials
- Naive Bayes
- Naive Bayes Tutorial
- Gauassian Naive Bayes Tutorial
- K-Nearest Neighbors
- K-Nearest Neighbors Tutorial
- Learning Vector Quantization
- Learning Vector Quantization Tutorial
- Support Vector Machines
- Support Vector Machines Tutorial
Ensemble Algorithms
- Bagging and Random Forest
- Bagged Decision Trees Tutorial
- Boosting and AdaBoost
- AdaBoost Tutorial
Path
1.1 Grouping Algorithms by Learning Styles
1.2 Grouping Algorithms By Similarity In Form and Function
1.3 How To Talk About Data In Machine Learning
- Approved America Staffing Resume Optimization will prepare and showcase your portfolio and top notch data science skills for an interlocked network workforce.
- Approved America Technology Training Graduates gain exclusive access to Approved America IQ internship and career matching through Approved America Staffing.
- Approved America Technology Training Schools delivers training, development, technical interview coaching, career search and placement, tools and interactive exercises to prepare you for your dream career as a Data Science.
- Approved America features career negotiation training with an Approved America Career Coach and LinkedIn Training.
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