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Become a Data Analysis Pro in the Age of AI

Master Advanced Data Analytics Techniques: Integrate AI and ML to Uncover Hidden Insights

Data Analysis: From Fundamental Insights to Advanced Strategies

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Here’s What Top Employers Want in Candidates — Do You Qualify?

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Professionals Who Understand the Role

Many candidates struggle to effectively demonstrate how their skills and experience align with a company's specific requirements.

Professionals Who Can Use Industry Tools

Employers expect candidates to be proficient in the tools they use daily, from threat detection to incident response.

Hands-On Experience in the Industry

While candidates may possess theoretical knowledge, they often lack the hands-on experience required for specific roles.

Mandatory Certifications for the Job

Employers require professionals to hold recognized certifications for industry compliance and skill validation.

Level 1: Beginner – Build Your Foundation

What You’ll Learn:
  • Learn basic data cleaning and visualization techniques.
  • Hands-on experience with beginner-friendly tools.
  • Introduction to machine learning concepts.
  • Geographic data handling for beginners.
  • Build a foundational understanding of cloud computing.
Real Tools,Real Practice :
Tidyverse Tidyverse
Jupyter Notebooks Jupyter Notebooks
Anaconda Anaconda
Orange Orange
KNIME KNIME
QGIS QGIS
Potential Use Cases:
  • Basic Data Reporting: Create clean, visual reports for business insights.
  • Sales and Marketing Dashboards: Visualize key metrics in marketing and sales for small businesses.
  • Geospatial Analysis: Handle location-based data to analyze business logistics, customer demographics, and geographic trends.
Certifications You’ll Be Ready For:
IBM Data Science Professional Certificate IBM Data Science
Professional Certificate
Microsoft Certified Azure AI Fundamentals Microsoft Certified:
Azure AI Fundamentals
TensorFlow Developer Certificate TensorFlow Developer Certificate
After completion of the course, Job Roles you are ready for: Data Analyst Marketing Data Analyst Financial Data Analyst Statistical Analyst Business Intelligence Analyst Data Visualization Specialist Database Administrator Operations Research Analyst GIS Analyst (Geographic Information Systems)

Level 2: Intermediate – Strengthen Your Skills

What You’ll Learn:
  • Build, train, and optimize machine learning models.
  • Work on big data tools to process large datasets.
  • Automate AI processes, from data preparation to model deployment.
  • Master intermediate-level cloud data analytics.
  • Explore techniques for complex spatial data analysis.
Real Tools, Real Practice :
Plotly Plotly
Hadoop Hadoop
Apache Spark Apache Spark
H2O.ai H2O.ai
DataRobot DataRobot
TensorFlow TensorFlow
PyTorch PyTorch
ArcGIS ArcGIS
Potential Use Cases:
  • Predictive Analytics: Build machine learning models to predict customer behavior, financial trends, or sales forecasts.
  • Big Data Analysis: Analyze large datasets in healthcare, retail, or finance for actionable insights.
  • Geospatial Insights: Use GIS tools to optimize supply chain routes, manage resources, or understand demographic patterns.
Certifications You’ll Be Ready For:
Microsoft Certified: Azure Data Scientist Associate Microsoft Certified:
Azure Data Scientist Associate
Cloudera Data Platform Generalist Certification Cloudera Data Platform
Generalist Certification
DASCA Senior Data Scientist (SDS) Data Science Council of America
(DASCA) Senior Data Scientist (SDS)
Google Cloud Professional Machine Learning Engineer Google Cloud Professional
Machine Learning Engineer
ArcGIS Specialist Certification ArcGIS Specialist Certification
After completion of the course, Job Roles you are ready for: Data Scientist Machine Learning Engineer Cloud Data Engineer Big Data Engineer Data Analytics Consultant Predictive Analytics Specialist GIS Analyst Fraud Detection Analyst Quantitative Analyst Data Operations Engineer Automation Engineer Cybersecurity Data Analyst

Level 3: Advanced – Master the Field

What You’ll Learn:
  • Develop complex AI and deep learning models with TensorFlow, PyTorch, and Keras.
  • Implement cloud data pipelines and storage solutions with Snowflake and Google Cloud.
  • Advanced relational and graph database management using Neo4j.
  • Work on parallel computing using Dask for efficient big data processing.
  • Build machine learning systems that can scale with GraphLab Create.
Real Tools, Real Practice :
TensorFlow TensorFlow
PyTorch PyTorch
Keras Keras
Snowflake Snowflake
Neo4j Neo4j
Dask Dask
GraphLab Create GraphLab Create
Potential Use Cases:
  • AI in Healthcare: Build deep learning models for disease prediction, medical image analysis, or personalized treatment.
  • Recommender Systems: Create personalized recommendation engines for e-commerce platforms, streaming services, or social media.
  • Fraud Detection: Use advanced machine learning to detect fraudulent transactions in real-time financial systems.
Certifications You’ll Be Ready For:
Certified Analytics Professional (CAP) Certified Analytics
Professional (CAP)
DASCA Principal Data Scientist (PDS) Data Science Council of America
(DASCA) Principal Data Scientist (PDS)
SAS Certified Data Scientist SAS Certified Data Scientist
Open Certified Data Scientist (Open CDS) Open Certified Data
Scientist (Open CDS)
DeepLearning.AI TensorFlow Developer Certificate DeepLearning.AI TensorFlow
Developer Certificate
Google Cloud Professional Data Engineer Google Cloud Professional
Data Engineer
NVIDIA Deep Learning Institute Certificate NVIDIA Deep Learning
Institute Certificate
After completion of the course, Job Roles you are ready for: Senior Data Scientist Deep Learning Engineer AI Specialist Data Engineer Big Data Architect Research Scientist (AI & Data) NLP Engineer (Natural Language Processing) Data Architect Data Analytics Consultant Cloud Data Architect Machine Learning Engineer (Advanced) Statistical Modeling Expert

Level 4: Expert – Become a Leader

What You’ll Learn:
  • Develop complex AI and deep learning models.
  • Implement cloud data pipelines and storage solutions.
  • Manage advanced relational and graph databases.
  • Work on parallel computing for efficient big data processing.
  • Build machine learning systems that can scale.
Real Tools, Real Practice :
DeepMind's Lab DeepMind's Lab
OpenAI's GPT-4 Playground OpenAI's GPT-4 Playground
Palantir Foundry Palantir Foundry
Google Cloud BigQuery Google Cloud BigQuery
Amazon SageMaker Amazon SageMaker
Rasa Rasa
Potential Use Cases:
  • Autonomous Systems: Apply reinforcement learning to robotics, self-driving cars, and automated decision-making.
  • Generative AI: Build cutting-edge applications for content creation, natural language understanding, and personalized user experiences.
  • Big Data Integration: Use Palantir Foundry for large-scale data collaboration and analysis across enterprises, governments, and defense sectors.
  • AI-Powered Virtual Assistants: Build advanced virtual assistants for businesses using Rasa, enabling automated customer service and personal assistance.
Certifications You’ll Be Ready For:
SAS Certified Advanced Analytics Professional SAS Certified Advanced
Analytics Professional
SAS Certified Professional: AI and Machine Learning SAS Certified Professional:
AI and Machine Learning
Certified Reinforcement Learning Expert Certified Reinforcement Learning Expert
Generative AI with Large Language Models Certification Generative AI with Large
Language Models Certification (OpenAI)
Palantir Foundry Certification Palantir Foundry Certification
AWS Certified Machine Learning Specialty AWS Certified Machine
Learning Specialty
After completion of the course, Job Roles you are ready for: Generative AI Specialist Reinforcement Learning Engineer AI Ethics Specialist Conversational AI Developer Senior Machine Learning Engineer Big Data Architect Automation Engineer (AI-Powered Systems) AI Research Scientist Data Scientist (Advanced) AI Product Manager Deep Learning Research Scientist Senior Quantitative Analyst

Data Analysis Learning Path

Key Courses We Offer: From Beginner to Expert

Each level incorporates AI and Machine Learning, providing you with future-ready data analysis skills for a rapidly evolving digital landscape.

Your Questions, Answered Clearly and Simply

A Data Analysis course equips you with the skills to analyze, interpret, and visualize data to drive informed decision-making in business and research. In today’s AI-driven world, data analysis is essential for industries like finance, healthcare, marketing, and more.

No prior experience is required. Our courses are designed to guide you from beginner to expert levels, ensuring you gain the necessary skills step by step. The foundational courses introduce data analysis, while more advanced levels integrate AI and Machine Learning concepts.

Each level is designed to build on the previous one, and the duration varies based on your existing skills and the time you dedicate to hands-on projects. Typically:
  • Level 1 (Beginner): 4–6 weeks
  • Level 2 (Intermediate): 8–10 weeks
  • Level 3 (Advanced): 10–12 weeks
  • Level 4 (Expert): 12–16 weeks
You can expect to become an expert in data analysis and AI/ML within 6–12 months, depending on your pace.

Yes, our course prepares you for globally recognized certifications such as Certified Analytics Professional (CAP), IBM Data Science Professional Certificate, Google Cloud Professional Data Engineer, and more, which are highly valued by employers worldwide.

The course is delivered online through a combination of live expert-led sessions, self-paced learning modules, and hands-on labs that simulate real-world data analysis and AI/ML projects.

Depending on the level, you will be prepared for certifications such as:
  • Level 1 (Beginner): IBM Data Science Professional Certificate, Microsoft Certified: Azure AI Fundamentals, TensorFlow Developer Certificate
  • Level 2 (Intermediate): Cloudera Data Platform Generalist Certification, Data Science Council of America (DASCA) Senior Data Scientist (SDS), Google Cloud Professional Machine Learning Engineer
  • Level 3 (Advanced): Certified Analytics Professional (CAP), Open Certified Data Scientist (Open CDS), DeepLearning.AI TensorFlow Developer Certificate
  • Level 4 (Expert): SAS Certified Advanced Analytics Professional, AWS Certified Machine Learning Specialty, Generative AI with Large Language Models Certification (OpenAI)

Certifications are highly valued by employers, as they validate your skills and knowledge in handling complex data, AI/ML integration, and advanced analytics. Many roles require certifications as part of their job qualifications.

Depending on the level you complete, you’ll be eligible for roles such as:
  • Level 1: Data Analyst, Business Intelligence Analyst, GIS Analyst, Data Visualization Specialist
  • Level 2: Data Scientist, Cloud Data Engineer, Machine Learning Engineer, Predictive Analytics Specialist
  • Level 3: Senior Data Scientist, AI Specialist, Data Architect, Research Scientist (AI & Data)
  • Level 4: Generative AI Specialist, AI Research Scientist, Senior Quantitative Analyst, Reinforcement Learning Engineer

Yes, we provide access to our Exclusive Learning Community Club (DELC), where job openings are regularly shared, and alumni are connected with recruiters and industry experts. Additionally, our real-world project experience ensures you’re job-ready upon completion.

Yes, all of our instructors are certified professionals with years of experience in data analysis, machine learning, and artificial intelligence. They have worked in various industries and bring real-world insights to the learning experience.

Salaries vary by role and location, but entry-level data analysts typically earn between $60,000–$80,000 annually. Advanced roles, such as Senior Data Scientists or AI Specialists, can command salaries upwards of $120,000–$150,000 or more, depending on the industry and expertise.

The course covers a wide range of topics, including:
  • Data cleaning, visualization, and reporting
  • Predictive modeling and machine learning integration
  • Big data processing with Hadoop and Spark
  • Geographic Information Systems (GIS) and geospatial analysis
  • AI and deep learning model development
  • Cloud data engineering with platforms like Snowflake and Google Cloud

You’ll work with industry-standard tools such as:
  • Level 1: Tidyverse, Jupyter Notebooks, QGIS
  • Level 2: TensorFlow, PyTorch, DataRobot, Hadoop
  • Level 3: Snowflake, Neo4j, Dask, GraphLab Create
  • Level 4: Palantir Foundry, DeepMind’s Lab, OpenAI GPT-4, Amazon SageMaker, Rasa

You will work on real-world projects and exercises in our virtual labs, providing practical experience with the latest tools in the industry. Projects increase in complexity as you progress through the levels, ensuring you apply your learning in real-world contexts.

We offer personalized mentorship and guidance from industry professionals. If you’re stuck, you can schedule one-on-one sessions with instructors to help you through difficult concepts or project challenges.

The learning path starts with foundational knowledge at the beginner level and progresses to advanced, specialized skills in AI, ML, and big data at the expert level. Each level includes certifications and tools that build on the previous one, ensuring continuous skill development.

The cost depends on the level you choose, the certifications included, and the tools used. Our team will guide you through personalized pricing based on your needs and career goals.

Yes, we offer flexible payment plans, discounts for early registration, group discounts, and financial aid options. Our support team can provide more details.

Certification exam fees are separate but discounted through our partner programs. All necessary tools and software for training are provided, with many offering free trials or student versions.

Yes, we offer a refund if you decide the course isn’t the right fit for you. Please note, however, that any license fees for software and tools issued during the course will not be refundable. For more information, please contact support.

Each level typically takes between 8 to 12 weeks to complete, depending on your pace and commitment. Flexible scheduling options are available to accommodate your needs.

Yes, our courses are designed to allow for self-paced learning. You can access materials anytime and progress through the levels at your convenience.

There are no strict prerequisites for enrolling, but familiarity with basic data analysis concepts and programming languages can be beneficial. Each level provides foundational knowledge to get you started.

You will have access to comprehensive course materials, virtual labs, mentorship, community forums, and industry-standard tools throughout your learning journey.

Yes, students can transfer between levels if they feel they are ready for a more advanced or introductory level. Please contact support for assistance with level transfers.

Yes, we provide tailored resources and mentorship for immigrants seeking to transition into the tech field. Our community fosters inclusivity and support, ensuring you feel welcomed throughout your learning journey.

Absolutely! This Data Analysis program is designed to provide the necessary skills and certifications to qualify for data analysis roles globally, including expertise in AI and machine learning, which are highly valued in the job market.

Yes! Many data analysis roles prioritize practical skills and certifications over formal degrees. This course ensures comprehensive training, preparing individuals for the demands of the field.

Definitely! This course is ideal for individuals transitioning into data analysis, equipping them with the essential skills and certifications required to enter the field.

Data analysts with AI and ML expertise are in demand across multiple sectors such as finance, healthcare, government, IT, telecommunications, to name a few. These industries rely on data insights, automation, and predictive analytics to inform strategic decisions.

This course is created to reflect the latest trends, tools, and methodologies used in data analysis and AI/ML. It ensures that you are learning cutting-edge techniques and technologies, making you highly competitive in the job market.

Yes, personalized mentorship is available throughout the course. Mentors are industry professionals who can guide you through difficult concepts, project work, and career advice.

You can schedule one-on-one sessions with mentors to discuss course materials, help with projects, and provide career advice. Mentorship is tailored to your learning and professional goals.

Yes, instructors are available for live sessions and online platforms to answer questions and provide real-time assistance during the course.

  • A laptop or desktop computer with at least 8GB of RAM.
  • Stable internet connection for live sessions and virtual labs.
  • Basic tools and software will be provided during the course.

No, all required tools and software will be provided during the course except your operating machine with licensed OS and Office applications. Our virtual labs are set up with everything you need to get started.

Learning AI/ML alongside Data Analysis enhances your ability to automate insights, identify patterns, and make more accurate predictions. It empowers you to analyze data more efficiently, improving decision-making and increasing the value you bring to data-driven roles.

You’ll gain hands-on experience with tools like:
  • Level 1: Tidyverse, Jupyter Notebooks, Anaconda, Orange, KNIME, QGIS
  • Level 2: Plotly, Hadoop, Apache Spark, H2O.ai, DataRobot, TensorFlow, PyTorch, ArcGIS
  • Level 3: Snowflake, Neo4j, Dask, GraphLab Create
  • Level 4: DeepMind's Lab, OpenAI's GPT-4 Playground, Palantir Foundry, Google Cloud BigQuery, Amazon SageMaker, Rasa

AI and ML in data analysis have various real-world applications, including predictive analytics, customer behavior modeling, fraud detection, healthcare diagnostics, and optimization of business processes. They help automate tasks, uncover insights, and improve decision-making across industries.

AI and ML certifications validate your expertise and demonstrate your ability to work with advanced data analysis tools. They enhance your career by making you more competitive in the job market, opening doors to roles in high-demand fields.

The biggest benefit is that you will gain hands-on experience, industry-recognized certifications, and job-ready skills, making you an attractive candidate for data analyst roles.

Yes, we have a vibrant Exclusive Learning Community Club (DELC) of learners where you can share ideas, ask questions, and collaborate on projects. You’ll also have access to networking opportunities with industry professionals and alumni.

Steps to Get Started

Book Appointment

Discuss with our Team

Team Enrollment

Payment Confirmation

Batch Allocation

Start of Program

What Experts Say

“Real-world projects are essential for mastering data analysis. My philosophy of 'Learn, Build, Teach' underscores the importance of hands-on experience for career growth, especially for students and immigrants”.


Brett Gamble
Founder- ITJOBBANDIT.COM
ITIL Certified, Tableau Data Scientist
Brett Gamble