Data Analyst Bootcamp with AI Training
Unlock your potential with the Data Analyst Bootcamp with AI! Gain real-world experience through hands-on exercises, assessments, and projects that showcase your expertise and prepare you for career success.
- Earn an average salary of $70,000 annually
Price : 6000 USD $2,999

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Introduction to Data Analyst Bootcamp with AI Training
Strategism is thrilled to introduce the next generation of our Data Analyst Bootcamp: the all-new Data Analyst Bootcamp with AI. This upgraded program is designed to help you stay ahead by integrating cutting-edge AI techniques into your data analysis journey. Whether you’re aspiring to become a skilled Data Analyst, start a data-driven business, or thrive as a freelance expert, this bootcamp is the ideal stepping stone to achieve your goals.
This enhanced program goes beyond conventional data analysis, empowering you to harness the power of AI for deeper insights and impactful outcomes. Alongside our already robust curriculum, you’ll gain complimentary access to the AI Engineer Bootcamp, which includes 288 hours of e-learning, over 130 hands-on exercises, 9 capstone projects, and 15 real-world case studies.
Delve into the core concepts of Machine Learning and learn how algorithms can analyze data and make accurate predictions. Additionally, master text data analysis, an essential skill in today’s AI-driven world.
The curriculum builds upon strong foundations in data analysis, starting with essential mathematical and statistical principles. You’ll learn data wrangling with industry-standard tools like Excel and SQL, enabling you to manage, analyze, visualize, and present data with confidence.
The Strategism Data Analyst Bootcamp with AI is designed to set you up for success. You’ll gain hands-on experience through practical exercises, regular assessments, and projects that showcase your expertise. Our program also includes comprehensive career support with personalized mentorship, guidance, and certification to help you secure your dream role in data analysis.
Join us for the Data Analyst Bootcamp with AI and become a highly sought-after professional, equipped with the expertise to unlock the power of AI in data analytics.
Why Should You Go For The Data Analyst Bootcamp


Across industries, decision-makers rely on actionable insights derived from real-world data to guide critical strategic and tactical decisions. Currently, there are nearly 400,000 Data Analyst positions listed on LinkedIn in the US alone, with the demand expected to grow by 25%, according to the U.S. Bureau of Labor Statistics. Pursuing a career in Data Analytics ensures long-term relevance and stability.
Data analysts play a vital role in capturing, analyzing, and interpreting data to uncover trends and patterns that address real-world challenges. These insights enable organizations to make informed decisions that align with their business goals. The Data Analyst Bootcamp equips you with the latest techniques and practical skills needed to excel in this field. By identifying meaningful patterns in data, analysts help businesses mitigate risks and make smarter, more profitable decisions.
As cloud computing, the Internet of Things (IoT), and Big Data continue to expand, the volume and quality of available data have significantly improved. Organizations now recognize the immense value of data analysts who can effectively harness this information. By mastering skills in acquiring, managing, storing, analyzing, and visualizing data, you’ll position yourself as an indispensable asset to any business seeking to unlock the full potential of its data resources.
What Do We Offer
Cutting-Edge Data Analytics Tools and Technologies You'll Learn





Course Syllabus
Learning Objectives:
- Understand the fundamentals of Excel, including basic functions and formulas.
- Perform statistical analysis with Excel.
- Master the use of PivotTables for efficient data analysis.
- Explore advanced data visualization techniques using Excel.
Topics Covered:
- Data Cleaning and Preparation.
- Using PivotTables and Grouping for Data Insights.
- Conducting Scenario and Sensitivity Analyses.
- Applying Lookup Functions and Merging Data.
- Creating Charts and Visualizations.
- Using the Data Analysis ToolPak for Statistical Functions.
Learning Objectives:
- Gain a comprehensive understanding of source code management using Git.
- Harness the potential of Git and GitHub for version control.
- Learn how to manage and collaborate on code like a professional.
Topics Covered:
- Introduction to Version Control and Git Basics.
- Using Git Command Line for Everyday Tasks.
- Key Git Commands for Version Management.
- Collaborative Coding with GitHub.
Learning Objectives:
- Develop expertise in Descriptive Statistics and Probability Theory.
- Understand various probability distributions, including Normal, Binomial, and Poisson.
- Learn Inferential Statistics to draw meaningful insights from data.
Topics Covered:
- Probability and Statistics Essentials.
- Linear Algebra Concepts for Data Analysis.
- Calculus Foundations for Data Science.
Learning Objectives:
- Learn essential SQL commands to interact with databases.
- Use filtering, operators, and functions to analyze and summarize data.
Topics Covered:
- SQL Fundamentals and Its Importance.
- Admin Commands for SQL Databases.
- Filtering Data with SQL Queries.
- Aggregation and Summary Functions.
- Understanding Relationships Between Tables.
- Combining and Analyzing Data Across Multiple Tables.
- Advanced SQL Techniques for Efficient Analysis.
- Master advanced SQL techniques for complex data analysis.
Learning Objectives:
- Start with Python programming basics.
- Utilize built-in and user-defined functions effectively.
- Work with powerful libraries like Pandas and NumPy.
- Create impactful visualizations using Python.
Topics Covered:
- Introduction to Python for Data Analytics.
- Key Programming Concepts: Strings, Data Structures, and Flow Control.
- Writing and Using Functions and Modules.
- File Handling in Python.
- Data Analysis with Pandas and NumPy.
- Using Regular Expressions for Data Processing.
- Data Visualization Techniques.
Learning Objectives:
Topics Covered:
- Exploratory and Confirmatory Data Analysis with Python.
- Advanced Pandas for Intermediate Users.
- Handling Unstructured Data in Python.
- API Integration for Data Retrieval.
- Parallel Computing with Dask.
- Advanced Visualizations: Seaborn, Plotly, and Bokeh.
- Learning Objectives:
- Get introduced to data visualization concepts and Tableau basics.
- Connect to various data sources in Tableau.
- Learn techniques for slicing and dicing data.
- Perform basic and advanced calculations in Tableau.
- Design, publish, and share interactive dashboards.
- Apply Excel basics and formulas to enhance Tableau workflows.
Topics Covered:
- Introduction to Tableau and Data Visualization.
- Tableau Building Blocks and Data Connections.
- Preparing and Managing Data in Tableau.
- Creating Basic and Advanced Visualizations.
- Slicing, Dicing, and Performing Calculations in Tableau.
- Formatting and Designing Dashboards.
- Publishing and Sharing Tableau Dashboards.

What You Will Learn
Mathematics and Statistics Fundamentals
Grasp the core principles of Mathematics and Statistics essential for Data Analytics.
Mastering Excel for Data Analytics
Learn how to use pivot tables and perform different types of data analysis using Excel worksheets
SQL for Data Analytics
Learn the fundamentals of databases and SQL, and how to execute basic SQL queries and perform data analysis.
Python Essentials for Data Analysis
Dive into Python basics, including functions and key libraries such as Pandas and NumPy, for data analysis.
Data Analysis with Python
Harness the power of Python programming to conduct exploratory data analysis and visualize data effectively.
Data Visualization with Tableau
Use Tableau to perform advanced calculations and create visually appealing dashboards that enhance data interpretation.
Skills You Will Gain
- Using Inferential Statistics
- Identifying interesting trends
- Building dashboards using Tableau
- Transforming datasets using Pandas
- Building visualizations with Seaborn
- Working with data from streaming APIs
- Designing basic statistical
- Finding answers for research questions
- Performing Descriptive Statistics on the data
- Implementing parallel computing techniques on datasets
- Using plotly and bokeh packages to build interactive plots
- Using Data Analysis tools like Excel, SQL, Python, and Tableau
What Our Customer Say About Us
Victor Ifediora
Caterina Vazquez
Shannon Wilson
Elizabeth Bolanos
Frequently Asked Questions
1. What are the prerequisites for this bootcamp?
All you need is the right mindset, logical thinking, and a curious attitude. We’ll take care of the rest!
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Workshop Experience
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