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Data Analytics Bootcamp​

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THE LEARNING EXPERIENCE

An unparalleled, structured pathway to success

Master Data Analytics in Just 4 Months

Our Data Analytics Bootcamp is designed to equip you with the skills and tools used by data professionals, blending live instruction, hands-on projects, and expert mentorship to ensure you gain real-world experience. This program provides structured learning, guiding you from data fundamentals to advanced analytics techniques.

Master Excel, Python, and R for data analysis

Work with PostgreSQL, MongoDB & relational databases

Create interactive visualizations with Tableau & Matplotlib

Apply machine learning for regression & classification

Curriculum

What you’ll learn in this Data Analytics Bootcamp

Discover the process of examining and evaluating raw data in order to bring meaning and insight that empowers intelligent decision-making, leading you to rewarding careers as:

Data Analyst
Operations Analyst
Data Engineer
Data Scientist
Business Intelligence Analyst

You’ll learn the tools and languages data analysts use, like:

  • Microsoft Excel
  • Phyton
  • Tableau
  • PostgreSQL
  • Pandas
  • dplyr
  • NumPy
  • ggplot2
  • Matplotib
  • Jupyter
  • MongoDB
  • tidyverse
  • Linux
  • Git
  • R
  • DBeaver

Core Modules

Foundations of Data Analytics

Module 1 provides a strong foundation in data analysis, covering the basics of data analysis, statistical theory, and essential tools...

Expand module

Microsoft Excel

Module 2 immerses students in Microsoft Excel, starting from basic functionalities to advanced data analysis features...

Expand module

SQL and Relational Databases

In this module, the student will be introduced to SQL and relational databases, essential for data storage, retrieval, and manipulation...

Expand module

R Programming

Module 4 focuses on R programming, a language widely used for statistical analysis and data visualization...

Expand module

Python Fundamentals

This module provides a comprehensive introduction to Python programming...

Expand module

Python for Data Analysis

This module teaches coding and data analytics skills including command line basics, GitHub version control, Python environment setup...

Expand module

Machine Learning - Regression

This module explores machine learning basics, focusing on linear regression for predicting outcomes...

Expand module

Machine Learning - Classification

This module covers machine learning classification, including model evaluation with confusion matrices and metrics like accuracy, precision, recall, and specificity...

Expand module

Tableau

This module focuses on mastering Tableau for data visualization and storytelling. You’ll learn how to transform raw data into interactive, insightful dashboards that drive decision-making...

Expand module

Capstone

Get hands on experience as a data professional

  • Tackle real-life data problems, enhancing your critical thinking and data skills.
  • Apply agile analytical methods, mirroring industry-standard practices.
  • Receive and implement feedback from mentors and peers to refine your skills.

Career Camp

Technical and Soft Skills Training

  • Proactive Career Support
  • Integrated Career Modules
  • Dedicated Career Coaches
  • AI-Powered Tools
  • Built-In Networking
  • Hands-On Practice
Learn More

Explore the curriculum that transforms careers.

Request Coursebook
LaunchPad

Real World Learning Employers Results

At Coding Temple, we don’t just teach tech skills—we prepare students for real jobs with real companies.

That’s why we built LaunchPad, an experiential training platform that will connect you with 40,000+ employers and thousands of active real-world projects, ensuring you graduate with hands-on experience that sets you apart in the job market.

Unmatched Real-World Learning Opportunities:

Boosted Placement Rates: Hands-on experience with real-world datasets and analytics tools ensures graduates enter the job market with practical skills that employers actively seek.

Stronger Portfolios & Resumes: Students build data-driven case studies, showcasing expertise in Python, SQL, and Tableau while demonstrating their ability to analyze and interpret business-critical insights.

Networking & Direct Employer Connections: Collaborating on live data projects with industry partners helps students gain exposure to hiring managers and build relationships that lead to career opportunities.

Reduces the ‘Experience Gap’ for Career Changers: By working on real analytics challenges, students develop industry-relevant experience, making the shift into data analytics roles smoother and more accessible.

5k

Projects

5,000 Active projects

Students have continuous access to 5,000 active real-world challenges from a variety of industries, guaranteeing practical experience.

40k+

Employers

40k Active Employers

Coding Temple students collaborate with real companies, gaining exposure to potential hiring managers, increasing your chances of networking with potential hiring managers.

Coding Temple ensures students don’t just learn, but also apply their knowledge in professional settings.

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our instructors

An amazing team of highly qualified professionals

Our instructors bring years of industry experience and a passion for teaching to every session. As experts in software development, data analytics, cybersecurity, and AI, they provide hands-on guidance, real-world insights, and personalized support in our interactive hybrid learning environment.

Othmane Benyoucef

Data Analytics Instructor

Get to know me

Hamza El-Husseiny

Data Analytics Instructor

Get to know me

Ken Wood

Data Analytics Instructor

Get to know me
Career

Future-proof your career with
our Lifetime Career Support

Our Career Services and support never expire. We are committed to your long-term career growth, equipping you with the tools and guidance to land your first data analytics role and beyond.

0 %

Employment Rate

$ 0 K

Salary Lift

We exist to get our learners hired in Data Analytics.

  • Personalized Career Mentorship
  • Hiring Partner Network
  • Data-Focused Technical Interviews
  • Exclusive Career Resources

Technical Coaching

  • CoderPad Technical Assessments
  • Mock Data Analytics Interviews
  • Data-Focused Technical Interview Coaching
  • Workshops on Business Intelligence Tools
  • Real-World Data Challenges & Case Studies
  • Guest Lectures from Expert Data Analysts

Soft Skills Coaching

  • Mock Interviews
  • Behavioral Training
  • Career Coaching
  • Salary Negotiation
  • LinkedIn Optimization
  • Resume Refinement
Our Testimonials

Here’s why students choose Coding Temple

Enrolling in Coding Temple's Data Analytics program was a game-changer for me. The curriculum is not just about the basics; it's a deep dive that equips you with skills that are seriously competitive in the job market. Now, let's talk about the real star of the show – my instructor, Katie Sylvia. Katie is a rockstar educator, blending patience, enthusiasm, and genuine care for her students in a way that takes the learning experience to a whole new level.
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Ann C.
The modules so far have been concise and easy to follow while being informative. The quizzes have helped to make sure the information is being understood. I also liked completing the project. I learn better by completing real world examples.
<img src="https://www.codingtemple.com/wp-content/uploads/2024/12/Frame-44.svg">
Karneisha D.
What really stood out was the community at Coding Temple. The collaborative environment fostered a sense of camaraderie among students and staff, creating a supportive network that went beyond the classroom.  I have graduated and this is still continuing day in and day out. Once your Alumni they still are just as supportive and about helping you grow as an individual. It’s truly amazing. 
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David D.
They will help you throughout the whole program, there is no moment that are going to feel alone. This is a life-changing decision and they would make it fun and dynamic to learn it and be part of the experience.
<img src="https://www.codingtemple.com/wp-content/uploads/2024/12/Frame-44.svg">
Benjamin D.
You guys changed my life and you in particular really helped me a few times and I just want to say thank you sincerely. I have a great career coach as well and going to land a better job soon and it’s because you guys at Coding Temple gave me that opportunity. I’m extremely grateful!
<img src="https://www.codingtemple.com/wp-content/uploads/2024/12/Frame-44.svg">
Stephen

Learn from passionate data analytics experts and mentors to boost your skills.

4.6

/5

Instructors

4.7

/5

Careers Services

4.8

/5

Curriculum

Tuition & Financing Options

Invest in your Future

Access to flexible payment options to make a life-changing education.

Most Savings

Total Tuition before discount

$12,495

Discount

-$2,500

Paid at enrollment

$9,995

Pay up front and save 20% on tuition

$12,495

$9,995

Most Flexible

Total Tuition before discount

$12,495

Deposit

$1,000

0% interest and no credit check

$12,495

Most Popular

Total Tuition before interest

$12,495

Enroll now, pay later. No deposit required.

$12,495

FAQ

Frequently asked questions

Data analytics is about examining and evaluating raw data to extract meaningful insights that support intelligent decision-making. You will learn how to turn raw data into meaningful insights, explore beginner and intermediate statistics, and coding basics for data manipulation and analysis techniques. Coding Temple’s data analytics course will turn you into an adept data analyst, ready to tackle the challenges of today’s data-driven world.

Data analytics is a rapidly growing field with opportunities across industries like finance, healthcare, and technology. The demand for skilled analysts continues to surge as companies rely on data-driven decisions to stay competitive. Entry-level roles like Data Analyst or Business Analyst offer competitive salaries ranging from $70,000 to $120,000, while advanced positions in data science or machine learning can exceed six figures. With Coding Temple’s hands-on curriculum, you’ll be prepared to thrive in this high-demand career path.

Coding Temple’s data analytics course is designed for people with no prior coding or data analytics experience. The program is designed to be challenging but rewarding. The instructors are supportive and always available to provide guidance. However, it is fast-paced, so students need to be prepared to work hard. The student to teacher ratio is about 1:4, which allows for more personalized attention.

The nine-module curriculum is project-based and includes a capstone project where students analyze and visualize real-life datasets. The curriculum also includes dive-deep into real-world datasets to extract valuable insights, learn advanced data visualization techniques to effectively communicate insights and trends, and work on a hands-on capstone project to solve complex data analysis challenges.

Coding Temple’s flexible learning model is designed for busy individuals. You can attend live, 1-hour daily sessions (recorded for later viewing) and dedicate around 3 hours a day to self-paced activities, including videos, assignments, and projects. This approach empowers you to learn on your terms.

We’re invested in your lifelong success! Career services include:

  • Early Career Prep: Workshops and alumni networking from day one.
  • Reverse Recruiters: Experts who find job opportunities tailored to your skills.
  • Interview Preparation: Mock interviews to build confidence and master both technical and behavioral questions.
  • Resume Optimization: Tailored feedback to highlight your strengths.
  • Exclusive Job Board (Prentus): AI-powered tools for a seamless job search.

Yes, we’re confident in our graduates! If you don’t secure a job within 9 months of completing the program, you’ll receive a full tuition refund (terms and conditions apply).

Our curriculum blends fundamental data analytics skills with advanced tools like Tableau, Python, and SQL, while emphasizing practical application through real-world projects. You’ll graduate with a comprehensive portfolio, including a capstone project showcasing your ability to analyze complex datasets and present actionable insights effectively.

Our alumni thrive in roles such as Data Analyst, Business Analyst, Data Scientist, and more. Many come from diverse backgrounds like education, finance, healthcare, and marketing, leveraging their new skills to transition into rewarding data-driven careers.

Ready to start your tech journey? We can’t wait to meet you!

Coding Temple believes in the power of education. We have built our curriculum around the most in-demand technologies and paired it with the most effective learning styles to prepare our students to be tomorrow’s leaders in technology.

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Data Analytics Bootcamp

Foundations of Data Analytics

10 hours

Module 1 provides a strong foundation in data analysis, covering the basics of data analysis, statistical theory, and essential tools. Students will gain an understanding of the data analytics process, basic statistical concepts, and practical skills for exploring relationships between variables.

Key elements of the module include:

Data Analytics Fundamentals:

Understanding the basics, applications, and ethics of data analytics.

Role Differentiation:

Distinguishing between Data Analysts, Data Scientists, and Data Engineers.

Data Handling and Analysis:

Managing datasets, calculating descriptive statistics, and analyzing variable relationships.

Data Visualization and Interpretation:

Visualizing data distributions, interpreting probability distributions, and conducting hypothesis testing.

Data Analytics Bootcamp

Microsoft Excel

10 hours

Module 2 immerses students in Microsoft Excel, starting from basic functionalities to advanced data analysis features. Students learn about data cleaning, transformation, and statistical analysis in Excel. The module includes practical exercises, quizzes, and lab assignments, culminating in a project that applies Excel in a real-world data analysis scenario.

Key elements of the module include:

Excel Proficiency:

Navigate Excel’s interface, apply functions for calculations and formatting, and manage missing data and duplicates.

Data Analysis and Visualization:

Use logical functions, create basic charts and graphs, and perform statistical analysis including linear regression.

Advanced Excel Features:

Utilize XLOOKUP, construct pivot tables and charts, and execute A/B tests for data-driven decision-making.

Data Standardization and Manipulation:

Standardize data formats, perform text manipulation, and create detailed visual representations like histograms and boxplots.

Learning Excel

20 hours

Module 2 immerses students in Microsoft Excel, starting from basic functionalities to advanced data analysis features. Students learn about data cleaning, transformation, and statistical analysis in Excel. The module includes practical exercises, quizzes, and lab assignments, culminating in a project that applies Excel in a real-world data analysis scenario.

Key elements of the module include:

  • Excel Proficiency: Navigate Excel’s interface, apply functions for calculations and formatting, and manage missing data and duplicates.
  • Data Analysis and Visualization: Use logical functions, create basic charts and graphs, and perform statistical analysis including linear regression.
  • Advanced Excel Features: Utilize XLOOKUP, construct pivot tables and charts, and execute A/B tests for data-driven decision-making.
  • Data Standardization and Manipulation: Standardize data formats, perform text manipulation, and create detailed visual representations like histograms and boxplots.

Data Analytics Bootcamp

SQL and Relational Databases

40 hours

In this module, the student will be introduced to SQL and relational databases, essential for data storage, retrieval, and manipulation. The module covers database creation, SQL queries, and advanced SQL features, culminating in a project utilizing SQL in a real-world data analysis context.

Key elements of the module include:

Database Concepts and Normalization:

Understand database concepts, the relational database model, and normalization techniques for efficient data organization.

SQL Query Proficiency:

Write and execute SQL queries (SELECT, INSERT, UPDATE, DELETE) and utilize advanced techniques like JOIN operations, subqueries, and aggregate functions.

Cloud-Based SQL Execution:

Execute SQL queries and manipulate large datasets within cloud-based platforms like BigQuery.

Database Management and Analysis:

Create and modify database tables, define data types, set constraints, and apply SQL for comprehensive data analysis and insight extraction.

Data Analytics Bootcamp

R Programming

20 hours

Module 4 focuses on R programming, a language widely used for statistical analysis and data visualization. Students learn about data manipulation, basic and inferential statistical analysis, and data visualization in R. The module includes hands-on exercises and a project applying R in a data analysis scenario.

Key elements of the module include:

R Environment and Syntax:

R Set up the R environment and understand R syntax, including installing and utilizing packages for additional functionalities.

Data Manipulation and Cleaning:

R Use dplyr and tidyr for data manipulation, cleaning, filtering, sorting, and transformation.

Statistical Analysis and Interpretation:

R Perform descriptive statistics, hypothesis testing, correlation analysis, regression analysis, ANOVA, and time-series analysis, and interpret results for real-world tasks.

Data Visualization:

R Create diverse types of plots and customize visualizations using ggplot2.

Data Analytics Bootcamp

Python Fundamentals

25 hours

This module provides a comprehensive introduction to Python programming. It covers fundamental data types, control flow structures, functions, and advanced techniques like list comprehensions. Students gain proficiency in string manipulation, loop iterations, modular code organization, and efficient list manipulation, preparing them for more complex programming tasks.

Key elements of the module include:

Command Line and Python Setup:

Use the command line for file and system management, and set up the Python environment with Anaconda.

Python Fundamentals:

Understand Python data types and structures, implement control flow structures, and handle errors.

Efficient Coding Techniques:

Write and modularize functions, master list comprehensions, and streamline loops with zip, enumerate, and advanced loop types.

Advanced Python Features:

Explore lambda functions for concise and functional programming.

Data Analytics Bootcamp

Python for Data Analysis

30 hours

This module teaches coding and data analytics skills including command line basics, GitHub version control, Python environment setup, Pandas for data manipulation, data visualization techniques, exploratory data analysis, and creating project README files for effective project documentation and communication.

Key elements of the module include:

Pandas Data Manipulation:

Understand Pandas data structures, perform data cleaning and preprocessing, and handle missing values and categorical data.

Exploratory Data Analysis (EDA):

Conduct basic and advanced EDA, select data subsets, and compute descriptive statistics.

Data Visualization:

Create and customize diverse visualizations, including bar graphs, histograms, scatter plots, line plots, heat maps, and box plots.

Project Documentation:

Craft informative README files detailing project purpose, functionality, installation instructions, and usage guidelines.

Data Analytics Bootcamp

Machine Learning - Regression

20 hours

This module explores machine learning basics, focusing on linear regression for predicting outcomes. We apply our skills to real-world challenges like predicting concrete strength and refine our techniques with Kaggle submissions. Through practical exercises, we develop a strong understanding of machine learning’s applications in data analysis and prediction tasks.

Key elements of the module include:

Machine Learning Fundamentals:

Understand core concepts of machine learning and differentiate between types, with a focus on supervised learning.

Linear Regression Modeling:

Apply linear regression for predictive modeling, interpret assumptions and coefficients, and make predictions using regression models.

Real-World Applications:

Apply machine learning techniques to real-world challenges, such as predicting concrete strength and home sale prices.

Advanced Regression Techniques:

Handle multicollinearity, fine-tune model parameters, and understand advanced techniques like polynomial regression and regularization (Ridge and Lasso).

Data Analytics Bootcamp

Machine Learning - Classification

20 hours

This module covers machine learning classification, including model evaluation with confusion matrices and metrics like accuracy, precision, recall, and specificity. It also includes implementing K-Nearest Neighbors (KNN) for classification and analyzing real-world datasets. Additionally, it focuses on extracting insights from customer behavior data for industry decision-making and creating interactive web applications using Streamlit for seamless sharing and accessibility.

Key elements of the module include:

Classification in Machine Learning:

Understand classification concepts and evaluate models using confusion matrices and metrics like accuracy, precision, recall, and specificity.

K-Nearest Neighbors (KNN):

Implement the KNN algorithm for classification tasks and analyze real-world datasets such as the Iris and breast cancer datasets.

Data-Driven Decision Making:

Extract insights from customer behavior data to inform decisions in industries like telecommunications.

Streamlit Applications:

Create and deploy interactive web applications using Streamlit for seamless sharing and user accessibility.

Data Analytics Bootcamp

Tableau

40 hours

This module focuses on mastering Tableau for data visualization and storytelling. You’ll learn how to transform raw data into interactive, insightful dashboards that drive decision-making. By the end of this module, you’ll be able to apply data visualization best practices and build complex dashboards, empowering you to effectively communicate insights.

Key elements of the module include:

Introduction to Tableau:

Get started with the basics of Tableau and its interface.

Data Visualization Best Practices:

Learn techniques for creating clear and effective visualizations.

Building Simple Dashboards:

Create your first dashboards to display data insights.

Advanced Chart Types in Tableau:

Explore a variety of chart types to present data in more dynamic ways.

Building Interactive Dashboards:

Develop interactive dashboards that allow users to explore data.

Embedding and Sharing Dashboards:

Learn how to embed dashboards in external platforms and share them with stakeholders.

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Software Engineering Bootcamp

Git and GitHub, Python Basics, and Codewars

40 hours

This module introduces version control with Git and GitHub, along with Python programming fundamentals. Students will also begin their practice with coding challenges on Codewars.

Key elements of the module include:

Git & GitHub Basics:

Learn version control, repository management, and collaboration with GitHub.

Python Fundamentals:


Understand strings, numbers, conditional statements, loops, and functions.

Exception Handling:


Learn how to handle errors and exceptions in Python.

Codewars Challenges:


Solve programming challenges to reinforce Python concepts.

Othmane Benyoucef

Data Analytics Instructor

Who am I

I am a versatile professional with a unique blend of expertise in data science, education, and industry leadership. My ability to bridge complex data challenges with clear insights has been shaped through a robust academic foundation and hands-on experience across diverse industries.

With a proven track record in strategic decision-making, curriculum development, and instructional design, I bring a powerful combination of technical acumen and pedagogical expertise to my role as a Data Analytics Curriculum Developer and Instructor. My work is centered around creating engaging, real-world learning experiences that empower students to excel in today’s data-driven environment.

Spearheading innovative projects at IT&B has allowed me to leverage advanced data analytics techniques, machine learning algorithms, and visualization tools to solve multifaceted challenges. These experiences have not only enhanced my technical skills but also honed my ability to communicate complex concepts effectively.

My diverse experience—ranging from founding a technology business to conducting cutting-edge research in data science—equips me with the unique perspective needed to lead students through transformative learning journeys. Whether I’m mentoring future data scientists or designing curricula that align with industry trends, my goal is to empower individuals with the tools and confidence necessary to thrive in today’s rapidly evolving landscape.

My Certifications

Education:

  • Doctorate Student in Data Science – University of Science and Technology of Oran (2012–2015)
  • Master’s Degree in Information Systems – University of Science and Technology of Oran (2008–2010)
  • Bachelor’s Degree in Computer Science – University of Science and Technology of Oran (2005–2008)

Awards & Recognitions:

  • German Exchange Service (Deutsche Akademischer Austauschdienst) Scholarship (July 2013)
  • Young Scholar / Researcher Student Best Paper Award, International Conference on Information Technology Interfaces, Dubrovnik, Croatia (June 2012)

Technical Expertise:

  • Proficient in Python, SQL, R, Java, JavaScript, and modern data visualization tools (Tableau, Power BI)
  • Experienced in machine learning, predictive analytics, data mining, ETL processes, and database design
  • Skilled in full-stack development, agile methodologies, and business intelligence

My Experience

Owner, IT&B (April 2009 – Present):

  • Founded and managed IT&B, transitioning from IT&B Algeria to IT&B USA, overseeing all aspects of business operations including project management, sales, and customer relations.

Data Analytics and Visualization Instructor, edX Boot Camps (October 2023 – February 2025):

  • Facilitate engaging classroom and virtual training sessions that blend theory with hands-on exercises.
  • Design and implement practical projects that reflect real-world data challenges.
  • Mentor students by integrating case studies and live examples from his extensive professional background.

Research Data Scientist, Database and Signal Analysis Lab at USTO MB-Oran (October 2010 – July 2015):

  • Pioneered advanced data mining methodologies and developed cutting-edge classification models within distributed computing environments.

Academic Roles:

  • Visiting Researcher at the Data Mining Lab, University of Louisville (February 2015 – April 2015)
  • Guest Scientist at the Chair For Methods in Empirical Education Research, Technical University of Munich (July 2013 – February 2014)
  • Adjunct Professor at the University of Oran and the University of Science and Technology of Oran (2012–2013), where he also supervised Master’s projects in data mining and visualization.

Teaching Philosophy

I believe that mastering data science is not just about acquiring knowledge but also about applying it effectively. My teaching approach is rooted in bridging the gap between theoretical concepts and practical application, ensuring students are well-equipped to tackle real-world challenges.

By incorporating current industry trends, case studies, and interactive projects that mirror actual business scenarios, I create a dynamic learning environment where critical thinking and innovation thrive. I am committed to fostering collaboration, encouraging students to explore creative solutions and apply analytical techniques to solve complex problems.

My dedication to continuous learning and effective communication helps inspire students to excel, driving success in the ever-evolving field of data science.

Hamza El-Husseiny

Data Analytics Instructor

Who am I

I am a data analytics and business intelligence instructor with extensive experience in data analysis, business strategy, and technical education.

My expertise spans Python, SQL, data visualization, machine learning, and business analytics, enabling me to guide students through hands-on projects and real-world applications.

As a dedicated mentor and educator, I am committed to making complex concepts accessible and fostering an engaging learning environment.

My Certifications

Academic Background:

  • Bachelor’s in Computer Science – Loughborough University
  • Master’s in Computer Science – Loughborough University

Certifications & Specializations:

  • AWS Certified Solutions Architect – Associate (Amazon Web Services, AWS)
  • AWS Cloud Solutions Architect Specialization (Coursera)
  • DevOps on AWS Specialization (Coursera)
  • Business Analytics & Data Analysis Certifications (Coursera, LinkedIn Learning)

My Experience

Data Analytics & Business Intelligence Training

  • Delivered lectures and group coaching on data analytics and business intelligence
  • Provided one-on-one mentorship, tracked student progress, and reviewed coursework
  • Guided students through project sprints, technical assessments, and real-world case studies
  • Developed curriculum materials focused on data analysis, business intelligence, and AI applications
  • Conducted live sessions to support students in achieving learning goals

Technical & Business Analysis Expertise

  • Worked on data-driven insights, market research, and financial modeling
  • Designed data interpretation scenarios, risk assessment models, and business strategy frameworks
  • Developed and maintained data analytics solutions using Python, SQL, and visualization tools
  • Combined data analytics & survey methodologies to provide tailored insights for decision-making

Instructional Design & Mentorship

  • Assisted in curriculum development and content review for data analytics programs
  • Conducted technical evaluations for prospective learners and instructors
  • Provided guidance on generative AI, foundation models, and emerging trends in data science

Teaching Philosophy

I am dedicated to bridging the gap between data analytics and business intelligence through real-world applications, hands-on learning, and personalized mentorship.

My expertise in data visualization, Python, SQL, and AI concepts ensures that students develop industry-ready skills to analyze, interpret, and leverage data for strategic decision-making.

Ken Wood

Data Analytics Instructor

Who am I

I am a seasoned data scientist specializing in machine learning, data analytics, and AI-driven business strategies.

With a strong background in cloud-based and SaaS technology solutions, I have developed and optimized machine learning models to transform datasets into actionable insights that drive decision-making.

I specialize in supervised and unsupervised learning techniques, feature engineering, and building machine learning pipelines on AWS SageMaker.

My Certifications

Academic Background:

  • MS, Electrical, Electronics & Communications Engineering – Worcester Polytechnic Institute
  • BS, Electrical Engineering – Purdue University

Certifications & Specializations:

  • Data Science Essentials Certificate – Cornell University
  • Natural Language Processing Specialization – DeepLearning.AI
  • Machine Learning Certificate – Cornell University
  • Data Engineering Specialization – IBM
  • Bayesian Statistics with R Specialization – Duke University
  • Applied Data Science in Python Specialization – University of Michigan
  • Big Data Specialization – UC San Diego
  • Building Machine Learning Pipelines in PySpark MLlib – Coursera
  • Data Science with Databricks/Apache Spark Specialization – Databricks
  • Deep Learning Specialization (Prof. Andrew Ng) – DeepLearning.AI
  • TensorFlow in Practice Specialization (Prof. Andrew Ng) – DeepLearning.AI
  • Time Series Analysis using R – Coursera

My Experience

Data Science & Machine Learning

  • Developed machine learning models to map subscriber behaviors and audience reach for advertising campaigns
  • Utilized Snowflake and AWS cloud platforms for data analysis and modeling
  • Created data-driven strategies to improve customer targeting and advertising effectiveness
  • Built advanced ML models to predict IT incidents using Azure & Google Cloud Platform (BigQuery, SQL)
  • Focused on feature engineering, forecasting, and anomaly detection for IT operations
  • Designed marketing channel attribution and ROI optimization models
  • Applied machine learning algorithms to analyze the marketing funnel, pipeline, and revenue performance

Data Analytics & Mentorship

  • Mentored 100+ students in Python, SQL, Excel, Tableau, and inferential statistics
  • Evaluated data science and analytics instructors on course delivery and effectiveness

Teaching Philosophy

I leverage my deep expertise in data science, machine learning, and cloud-based analytics to bridge the gap between theory and practical applications.

My courses emphasize hands-on learning, real-world projects, and industry-aligned skill development to prepare students for successful careers in data analytics and AI-driven decision-making.

End-of-Year Savings Alert! Big price drop on all our programs – save up to $2,500! 🎉

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