Data Science Training Online in Jacksonville

Best Data Science Bootcamp Training in Jacksonville and Miami, Florida

The demand for data scientists in Florida is skyrocketing, especially in tech-driven cities like Jacksonville and Miami. With industries ranging from healthcare and finance to logistics and retail relying on data-driven insights, professionals equipped with advanced skills in data science, data analytics, data engineering, and ML/AI are in high demand. For jobseekers, choosing the best data science bootcamp in Florida is critical—not just for learning, but for securing employment. That’s where SynergisticIT’s Job Placement Program (JOPP) stands apart.

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Why Data Science and Data Analytics Are Important in Florida

Florida’s economy is diverse, with strong sectors in healthcare, banking, tourism, logistics, and retail. Each of these industries generates massive amounts of data daily.

  • Healthcare (Jacksonville & Miami): Hospitals and research centers require predictive analytics to improve patient outcomes.
  • Finance (Miami’s fintech hub): Banks and insurance companies use machine learning for fraud detection and risk modeling.
  • Logistics & Retail (Jacksonville’s port and Miami’s retail giants): Supply chain optimization and customer behavior analysis depend on advanced analytics.

Learning data science and data analytics is no longer optional—it’s a necessity for anyone aiming to thrive in Florida’s competitive job market.

Florida offers a wide range of opportunities for data scientists across industries such as consulting, healthcare, finance, and technology, with Jacksonville standing out as a major hub. In Jacksonville, firms like Deloitte, PwC (PricewaterhouseCoopers), EY (Ernst & Young), Intercontinental Exchange (ICE), Scribd, Inc., Launch Potato, Acosta Group, The Energy Authority (TEA), Noblesoft Solutions, Mayo Clinic, Nemours Children’s Health, Ascension Health, Bank of America, Molina Healthcare, and TD Bank actively recruit data professionals for roles in analytics, AI, and machine learning. Beyond Jacksonville, other Florida cities also host strong demand: Citrix in Fort Lauderdale, Ultimate Kronos Group (UKG) in Weston, Magic Leap in Plantation, Florida Blue statewide, Raymond James Financial in St. Petersburg, L3Harris Technologies in Melbourne, Lockheed Martin and Disney in Orlando, Johnson & Johnson in Tampa, and Publix Super Markets in Lakeland all hire data scientists to support projects ranging from healthcare analytics and financial modeling to defense, retail, and customer experience optimization.

Data scientist salaries in Florida vary widely depending on the company, industry, and level of experience, ranging from entry-level research positions to senior AI and machine learning roles. In Jacksonville, firms like Deloitte, PwC, EY, Intercontinental Exchange (ICE), Scribd, Launch Potato, Acosta Group, The Energy Authority (TEA), Noblesoft Solutions, Mayo Clinic, Nemours Children’s Health, Ascension Health, Bank of America, Molina Healthcare, and TD Bank offer compensation that spans from around $56K for junior healthcare research roles up to $200K+ for advanced AI/ML positions in finance and consulting. Across other Florida cities, companies such as Citrix, Ultimate Kronos Group (UKG), Magic Leap, Florida Blue, Raymond James Financial, L3Harris Technologies, Lockheed Martin, Disney, Johnson & Johnson, and Publix Super Markets also provide competitive salaries, with ranges typically between $90K and $150K, and senior roles at Disney, Lockheed Martin, and UKG exceeding $200K.

 

  • Exponential Data Growth: Businesses are generating massive amounts of structured and unstructured data. Extracting insights from this data is critical for innovation and efficiency.
  • AI & Machine Learning Integration: Data scientists are essential for building, training, and deploying AI models. As generative AI, NLP, and deep learning expand, specialized data science skills will remain indispensable.
  • Job Security & Growth: Even during tech layoffs, data science roles have remained resilient because they are tied directly to business growth and efficiency.

According to the U.S. Bureau of Labor Statistics, data scientist employment is projected to grow 34% from 2024 to 2034, much faster than average for all occupations. That translates to about 23,400 new openings per year. This growth is driven by the explosion of big data, AI adoption, and the need for predictive analytics in nearly every sector.

Emerging Tech Skills Companies in Florida Demand

Employers in Florida are increasingly asking for professionals skilled in:

  • Machine Learning & AI: TensorFlow, PyTorch, Scikit-learn
  • Data Engineering: Apache Spark, Hadoop, Kafka, Snowflake
  • Data Analytics: SQL, Tableau, Power BI, Excel advanced analytics
  • Programming & Cloud: Python, R, AWS, Azure, Google Cloud

Simply learning data science or ML/AI is not enough. Companies want candidates who can handle end-to-end data pipelines—from engineering and cleaning data to building predictive models and visualizing insights.

 

Why SynergisticIT Is Different from Other Bootcamps

Not all coding bootcamps are equal. Many promise job guarantees but fail to deliver, leaving students to fend for themselves in the job market. SynergisticIT’s best data science bootcamp training in Jacksonville and Miami, Florida is different because:

  • 15+ Years in Tech Industry: Proven track record of training and placing candidates.
  • Comprehensive Curriculum: Covers data engineering, data analytics, ML/AI, and data science in one program.
  • Job Placement Program (JOPP): Unlike other bootcamps, SynergisticIT actively markets candidates, schedules interviews, and works with them until they get hired.
  • Real Projects & Certifications: Hands-on projects, interview preparation, and certifications make candidates job-ready.

Explore SynergisticIT’s Job Placement Program (JOPP) and SynergisticIT’s Data Science JOPP to see how their approach is different.

 

 

Reasons to Learn Data Science

Let’s look at the top reasons to pursue a Data Science career in Florida:

Data scientists are and will continue to be in high demand in Jacksonville, Miami, and across the USA because industries are increasingly dependent on data-driven decision-making, artificial intelligence, and advanced analytics to stay competitive.

  • Jacksonville, FL: The city’s booming tech sector is fueled by healthcare, fintech, and logistics. Companies like Baptist Health, FIS, and Dun & Bradstreet are expanding operations, driving demand for professionals who can analyze patient data, financial transactions, and supply chain efficiency. Jacksonville’s tech workforce is growing at one of the fastest rates nationwide, with AI and machine learning roles offering salaries up to $200K.
  • Miami, FL: Miami has become a fast-growing tech hub, with a 40% increase in tech jobs over the past five years. Industries like tourism, healthcare, finance, and logistics rely heavily on data science to personalize customer experiences, optimize healthcare outcomes, detect fraud, and streamline shipping operations. The city’s vibrant startup ecosystem and initiatives like Miami Tech Works are building a sustainable pipeline of talent.

Why Demand Will Continue in the Future

  • Hybrid Skill Demand: Employers increasingly want professionals who combine technical expertise (Python, SQL, ML frameworks) with business acumen and communication skills, making data scientists uniquely valuable.

The demand for data scientists in Jacksonville and Miami reflects local industry strengths in healthcare, finance, and logistics, while the national outlook shows explosive growth across all sectors. With AI adoption accelerating and data volumes expanding, data science will remain one of the most future-proof careers in the U.S.

  • Most Sought-After Skill in IT: Of Late, there has been a 29% increase in the demand for skilled Data Scientists. However, the job applicants for data-related jobs are growing at a slower pace of 14%. It underlines the acute shortage of competent Data Science professionals and shows a gap between demand and supply. You can fill that gap and meet the rising demand for trained Data Scientists by getting upskilled in Data Science training in Jacksonville. 

  • Bigger Paychecks: Data Science training is the shortcut to securing rewarding jobs with higher salaries. The average salary of Data Scientists ranges between $104,000 to $155,000 per annum. It may further increase based on your experience, skills, background, or location. So, if you want to improve your earning potential, you must consider enrolling in a Data Science Bootcamp.

Data Science Training in Jacksonville
  • Plenty of Jobs: The U.S. Bureau of Labour Statistics has predicted a 28% boost in Data Science jobs by the end of 2026. It will create over 11.8 million new data-related jobs. Thus, learning Data Science seems to be the safest bet for your career.

  • An opportunity to work in Fortune 500 Companies: Nowadays, leading tech giants like Apple, Amazon, eBay, Facebook, Microsoft, Google, and others hire Data Scientists for business expansion and mitigating the risk of losing their customer base. You can win yourself a chance to get recruited in such companies by taking Data Science training in Jacksonville.

A Sneak Peek of our Data Science Course

The Data Science Job Placement Program (JOPP)

SynergisticIT’s Data Science JOPP is not just a bootcamp—it’s a staffing + training solution. Instead of leaving graduates to search for jobs alone, SynergisticIT connects them directly with employers.

Tech Stack Covered in JOPP

  • Data Science: Python, R, Pandas, NumPy, Matplotlib
  • ML/AI: TensorFlow, PyTorch, Keras, NLP, Deep Learning models
  • Data Analytics: SQL, Tableau, Power BI, Excel advanced analytics
  • Data Engineering: Hadoop, Spark, Kafka, Snowflake, ETL pipelines
  • Cloud Platforms: AWS, Azure, Google Cloud
  • Projects & Certifications: End-to-end projects, interview prep, and certifications

This holistic approach ensures candidates are job-ready across multiple domains, not just one.

The Data Science Job Placement Program (JOPP)

SynergisticIT’s Data Science JOPP is not just a bootcamp—it’s a staffing + training solution. Instead of leaving graduates to search for jobs alone, SynergisticIT connects them directly with employers.

Placement Success and Salaries

SynergisticIT’s candidates are hired by top companies at salaries ranging from $95K to $155K. Employers include:

  • Tech Giants: Visa, Apple, PayPal, Cisco Systems, Dell
  • Finance Leaders: Wells Fargo, Capital One, Bank of America, Western Union
  • Healthcare & Retail: Walgreens, Humana, Walmart Labs, AutoZone
  • Telecom & Cloud: Verizon, T-Mobile, SAP, Intuit
  • Consulting & Enterprise: Deloitte, USAA, Carfax, Hitachi, Ford

These placements prove that SynergisticIT’s program is not just training—it’s a career launchpad.

Why Choose SynergisticIT Over Other Bootcamps

Many jobseekers waste time and money on 4–5 different coding bootcamps or cheaper training companies that promise jobs but fail to deliver. SynergisticIT eliminates this problem by offering a single, comprehensive program that covers everything employers demand.

  • Active Marketing of Candidates: SynergisticIT doesn’t stop at training—it markets candidates to employers.
  • Interview Scheduling: Direct connections with hiring managers ensure candidates get interviews.
  • Job Assistance Until Placement: The program continues until candidates are hired.

Introduction to Data Science with Python

  • What is Data Science & Analytics?
  • Common Terms in Analytics
  • What is Data & its Classification?
  • Relevance in industry and need of the hour
  • Types of problems and business objectives in various industries
  • Critical success drivers
  • Overview of analytics tools & their popularity
  • Analytics Methodology & problem-solving framework
  • List of steps in Analytics projects
  • Build Resource plan for analytics project
  • Finding the most appropriate solution design for the given problem statement
  • Project plan for Analytics project & key milestones based on effort estimates
  • How leading companies are harnessing the power of analytics?
  • Why Python for data science?

Python Introduction & Data Structures

  • Python Tools & Technologies
  • Benefits of Python
  • Important packages (Pandas, NumPy, SciPy, Scikit-learn, Seaborn, Matplotlib)
  • Why Anaconda?
  • Installation of Anaconda & other Python IDE
  • Python Objects, Numbers & Booleans, Strings, Container Objects, Mutability of Objects
  • Jupyter Notebook
  • Data Structures
  • Python Practical Session / Task

Numerical Python (NumPy)

  • Data Science and Python
  • What is NumPy?
  • NumPy Operations
  • Types of Arrays
  • Basic Operations
  • Indexing & Slicing
  • Shape Manipulation
  • Broadcasting
  • NumPy Practical Session / Task

Pandas Data Analysis

  • Why Pandas?
  • Pandas Features
  • Pandas File Read & Write Support
  • Data Structures
  • Understanding Series
  • Data Frame
  • Pandas Practical Session / Task Data Standardization
  • Missing Values
  • Data Operations
  • NumPy Practical Session / Task

Matplotlib & Seaborn Data Visualization

  • What is Data Visualization?
  • Benefits & Factors of Data Visualization
  • Data Visualization Considerations & Libraries
  • Data Visualization using Matplotlib
  • Advantages of Matplotlib
  • Data Visualization using Seaborn
  • What is a Plot and its types?
  • How to Plot with (x,y)?
  • How to Control Line Patterns and Colors
  • How to Implement Multiple Plots?
  • Matplotlib Practical Session / Task

Data Manipulation: Cleansing – Munging

  • Data Manipulation steps (Sorting, filtering, merging, appending, derived variables, etc)
  • Filling the missing values by using Lambda function and Skewness.
  • Cleansing Data with Python

Data Analysis: Visualization Using Python

  • Introduction exploratory data analysis
  • Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas, etc)
  • Univariate Analysis (Distribution of data & Graphical Analysis)
  • Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)
  • Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ density etc)
  • Descriptive statistics, Frequency Tables & summarization

Introduction to Artificial Intelligence (AI) & Machine Learning (ML)

  • What is Artificial Intelligence & Machine Learning?
  • What is Big Data?
  • Understanding the difference between Artificial Intelligence, Machine Learning & Deep Learning
  • Artificial Intelligence in Real World-Applications

Machine Learning Techniques & Algorithms

  • Types of Machine Learning
  • Machine Learning Algorithms
  • Hyper parameter optimization
  • Hierarchical Clustering
  • Implementation of Linear Regression
  • Performance Measurement
  • Principal component Analysis
  • How Supervised & Unsurprised Learning Model Works?
  • Machine Learning Project Life Cycle & Implementation
  • What is Scikit Learn, Regression Analysis, Linear Regression?
  • Difference between Regression & Classification
  • What is Logistic Regression and its implementation?
  • Best Machine Learning Approach

Decision Tree and Random Forest Algorithm

  • What is a Decision Tree and how it works?
  • What is Entropy, Information Gain, Decision Node?
  • In-depth study of Random Forest and understanding how it works?

Naive Bayes and KNN Algorithm

  • What is Naïve Bayes?
  • Advantages & Disadvantages of Naïve Bayes
  • why KNN?
  • Practical Implementation of Naïve Bayes
  • What is KNN and how does it work?
  • How do we choose K?
  • Practical Implementation of KNN Algorithm

Support Vector Machine Algorithm

  • What is Support Vector Machine (SVM)?
  • How Does SVM Work?
  • Applications of SVM
  • Why SVM?
  • Practical Implementation of SVM

Model Deployment & Tableau

  • Flask Introduction & Application
  • Django end to end
  • Working with Tableau
  • Data organisation
  • Creation of parameters
  • Advanced visualization
  • Dashboard data presentation

Introduction to Statistics

  • Descriptive Statistics
  • Sample vs Population Statistics
  • Random variables
  • Probability distribution functions
  • Expected value
  • Normal distribution
  • Gaussian distribution
  • Z-score
  • Central limit theorem
  • Spread and Dispersion
  • Hypothesis Testing
  • Z-stats vs T-stats
  • Type 1 & Type 2 error
  • Confidence Interval
  • ANOVA Test
  • Chi Square Test
  • T-test 1-Tail 2-Tail Test
  • Correlation and Co-variance

Introduction to Predictive Modelling

  • The concept of model in analytics and how to use it?
  • Different Phases of Predictive Modelling
  • Popular Modelling algorithms
  • Different kinds of Business problems - Mapping of Techniques
  • Common terminology used in Modelling & Analytics process

Data Exploration for Modelling

  • Visualize the data trends and patterns
  • Identify missing data & outliers’ data
  • EDA framework for exploring the data & identifying problems with the data by the help of pair plot.
  • What is the need for structured exploratory data?

Data Preparation

  • Merging
  • Normalizing the data
  • Feature Engineering
  • What is the need for Data preparation?
  • Aggregation/ Consolidation - Outlier treatment - Flat Liners - Missing Values-Dummy creation - Variable Reduction
  • Variable Reduction Techniques - Factor & PCA Analysis
  • Feature Selection
  • Feature scaling using Standard Scaler
  • Label encoding

Ensemble Learning Techniques

  • In-depth study of Ensemble Learning with Real Examples
  • How to Reduce Model Errors with Ensembles
  • Understanding Bias and Variance
  • Different Types of Ensemble Learning Methods
  • Feature Selection
  • Feature scaling using Standard Scaler
  • Label encoding

Web Scraping using Python Beautiful Soup

  • What is Web Scraping & Why Web Scraping?
  • Web Scraping using Beautiful Soup Practical Session / Task
  • Difference Between Web Scraping Software Vs. Web Browser
  • Web Scraping using Beautiful Soup Practical Session / Task
  • Web Scraping Considerations & Tools
  • Why Beautiful Soup?
  • Common Data & Page Formats on the Web
  • Practical Implementation of Web Scraping
  • Web Scraping Process
  • What is a Parser?
  • Importance of Parsing
  • What are the various Parsers?
  • How to Navigate the Parsers?
  • How to take Output – Printing & Formatting

Time Series Analysis

  • Why Time Series Analysis?
  • What is Time Series?
  • Time Series Components (Seasonality, Trend, Level & Cyclicity) and Decomposition
  • Classification of Techniques like Pattern based or Pattern less
  • Basic to Advance level Techniques (Averages, AR Models, Smoothening, ARIMA, etc)
  • Use Cases of Time Series Analysis
  • When Not to Use Time Series Analysis?
  • Understanding Forecasting Accuracy - MAPE, MAD, MSE, etc
  • Time Series Analysis Case Study - Practical Session / Task

Deep Learning

  • What is deep learning
  • The neuron
  • How do neural networks work?
  • Back propagation
  • ANN in Python
  • What are convolutional neural networks?
  • Installing Tensor Flow & Keras
  • CNN in Python
  • Activation function & Epoch

Natural Language Processing (NLP) & Text Mining

  • What is Natural Language Processing (NLP) & Why NLP?
  • NLP with Python
  • Sentiment analysis
  • Bags of words
  • Stemming
  • Tokenization
  • What is Text Mining?
  • Text Mining & NLP
  • Benefits, Components, Applications of NLP
  • NLP Terminologies & Major Libraries
  • NLP Approach for Text Data
  • What is Sentiment Analysis?
  • Steps for Sentiment Analysis
  • Sentiment Analysis Case Study - Practical Session / Task
  • Practical Implementation of NLP
  • NLP Case Study - Practical Session / Task

Market Basket Analysis

  • What is Market Basket Analysis & how it is used?
  • What is Association Rule Mining?
  • What is Support, Confidence & Lift
  • An Example of Association Rules
  • Market Basket Analysis Case Study - Practical Session / Task
Data Science Training Program in Jacksonville

Who can attend our Data Science Training in Jacksonville ?

This career-focused Data Science training is for anyone who wants to build a career in this lucrative industry. You can enroll in our training if you are:

An individual working on reporting tools, BI, or data warehousing

Professional with a logistics or analytical background

Economist, Mathematician, or Statistician

Software developer/business analyst wanting a career shift

Fresher or a college graduate/undergraduate

Career Prospects after Data Science Training

With more and more companies harnessing AI, Big Data, & Machine Learning technologies, the demand for Data Science professionals has accelerated. So, professionals skilled in Data Science are likely to get abundant both in terms of money and growth opportunities. Let’s look at the prospective career options after Data Science training in Jacksonville:

Data Engineer ($125,732)

BI Solutions Architect ($120,539)

Analytics Manager ($112,467)

Data Scientist ($120,103)

Statistician ($97,643)

BI Specialist ($90,286)

BI Engineer ($117,044)

Data Visualization Developer ($105,501)

Top paying Data Science jobs in Jacksonville

Business Analytics Specialist ($84,601)

Big Data Engineer ($103,092)

Start acquiring valuable Data Science and Data Analyst skills by training at the best online Data Science Bootcamp.

Online Flexibility

Another advantage is that SynergisticIT’s online data science bootcamp in Florida can be done from anywhere in the USA. Whether you’re in Jacksonville, Miami, or another city, you can access the same training, projects, and job placement support.

There may be hundreds of data science bootcamps in Florida, but if your goal is to get hired after training, there is only one choice: SynergisticIT’s best data science bootcamp training in Jacksonville and Miami, Florida. With over 15 years in the tech industry, a proven Job Placement Program, and a curriculum that covers data engineering, data analytics, ML/AI, and data science, SynergisticIT ensures that jobseekers don’t just learn—they get hired.

SynergisticIT’s best data science bootcamp training in Jacksonville and Miami, Florida is the sure-shot way of ensuring a jobseeker can secure employment in today’s competitive market.

SynergisticITHome of the Best Data Scientists and Software Programmers!

train to grow- Machine Learning

FAQs on Data Science Training

What Our Candidates Say About Us ?

Google Reviewer

Being an international student in USA and realizing that I was on the verge of completing my CS degree with not enough experience or skills to crack the interviews I was desperate for some kind of breakthrough. I started looking for a tech Bootcamp which could work with my study schedule and yet offer me…

Minh Ho

Good place for anyone struggling to find a technology job with bigger name clients. I worked with them for some time like a year back or so and after my experience with them I had upgraded my coding skills to the standards of major it organizations. Synergisticit is in my opinion one of the very…

Menglee G.

Synergistic IT was the best decision I made for my career. During my time here, I worked on multiple projects and learned a lot of high demand skills for the competitive tech industry. They have amazing trainers who have lots of experience. I would recommend it to anyone who wants to become a professional in…

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