AI & Machine Learning in Dallas, Texas, USA

Artificial Intelligence (AI) and Machine Learning (ML) are transforming industries by enabling computers to learn from data, make decisions, and perform tasks that traditionally required human intelli...
563+ Enrolled 25 Modules 64 Lessons
5.0
AI & Machine Learning in Dallas, Texas, USA

Course Description

What is Artificial Intelligence & Machine Learning?


Artificial Intelligence (AI) and Machine Learning (ML) are transforming industries by enabling computers to learn from data, make decisions, and perform tasks that traditionally required human intelligence. AI includes various subfields such as deep learning, natural language processing (NLP), computer vision, and predictive analytics.

Machine Learning, a subset of AI, focuses on developing algorithms that allow computers to analyze patterns and make predictions without explicit programming. Today, AI & ML power innovations like chatbots, recommendation systems, self-driving cars, fraud detection, and more.


This program is designed to give students a strong foundation in AI & ML concepts, practical coding skills, and real-world applications to prepare for high-paying tech careers.


Course Description


Our Artificial Intelligence & Machine Learning Training Program is a hands-on, practical course that equips students with the essential knowledge and tools required to develop AI-driven applications.

Students will learn Python programming, data science techniques, deep learning, neural networks, natural language processing, and model deployment. The program includes real-world projects and industry use cases to ensure practical learning.

By the end of this course, students will be able to design, train, and deploy AI/ML models for various applications, making them job-ready for roles in data science, AI development, and automation engineering.


Why Choose This Course?


✅ High-Demand Skills – AI & ML professionals are among the most sought-after in the tech industry.

✅ Lucrative Career Opportunities – AI engineers and ML specialists earn top salaries worldwide.

✅ Real-World Applications – Learn by working on practical projects used in finance, healthcare, e-commerce, and automation.

✅ Beginner-Friendly & Advanced Learning – Whether you’re new to coding or an experienced developer, this course is structured to help you grow.


Who Should Enroll?


✔️ Software developers, engineers, and data analysts looking to upskill

✔️ Students and professionals aiming for careers in AI, ML, and data science

✔️ Entrepreneurs and business owners who want to integrate AI-driven solutions into their businesses

✔️ Anyone passionate about technology and the future of artificial intelligence


Course Benefits & Key Takeaways


🔹 Master Python programming, data science, and AI frameworks

🔹 Learn machine learning, deep learning, and neural networks from scratch

🔹 Gain hands-on experience with TensorFlow, Keras, Scikit-Learn, and PyTorch

🔹 Work on real-world AI projects, including chatbots, image recognition, and recommendation engines

🔹 Get career support, including resume building, job assistance, and interview prep


Course Roadmap


✅ Step 1: Enroll in the Program – Get access to AI & ML training with expert mentorship.

✅ Step 2: Complete Course Modules – Master AI concepts through theory and hands-on coding exercises.

✅ Step 3: Work on Real-World AI Projects – Build and deploy AI applications to showcase your skills.

✅ Step 4: Job Market Preparation – Resume building, mock interviews, and career guidance.

✅ Step 5: Land a Job in AI & ML – Start your career in AI development, data science, or automation.


Potential Jobs & Salary in the USA


AI & ML professionals are in high demand, and companies across industries are actively hiring AI talent.


Job Roles:


🤖 Machine Learning Engineer – Design and optimize AI models for automation and decision-making.

📊 Data Scientist – Analyze large datasets to drive business insights and strategy.

🔎 AI Research Scientist – Conduct research in deep learning, NLP, and advanced AI models.

🎨 Computer Vision Engineer – Develop AI-powered image and video analysis applications.

💬 NLP Engineer – Build and enhance AI models for chatbots, speech recognition, and language translation.


Salary & Job Growth:


💰 Average Salary: $100,000 - $150,000 per year

📈 Job Growth: Expected to grow 22% by 2030 (one of the fastest-growing tech fields)

💼 Top Hiring Companies: Google, Microsoft, Amazon, Tesla, IBM, Meta, Startups, and FinTech Companies


Start Your AI & ML Journey Today!


🚀 Enroll in the Artificial Intelligence & Machine Learning Course to master the skills that power the future of technology. Gain hands-on experience, industry insights, and job-ready AI expertise.

📅 Limited spots available – Sign up now!

What you'll learn

Module 3: Machine Learning Fundamentals
Module 4: Deep Learning & Neural Networks
Module 5: Natural Language Processing (NLP)
Module 6: AI Model Deployment
Module 7: AI Capstone Project & Career Support

Curriculum

Class 1: Introduction to Python + installation

4 lectures • 0m

What is Python? Why use it?
Installing Python, using Jupyter Notebook and VS Code
Basic syntax: Variables, data types, operators
Hands-on: Writing a simple Python script – Hello world
Class 2: Control Flow & Loops

3 lectures • 0m

Conditional statements: if, elif, else
Loops: for and while
Hands-on: Writing a number guessing game
Class 3: Functions and Modules

4 lectures • 0m

Defining functions, return values, parameters
lambda functions, built-in functions
Importing and using Python modules
Hands-on: Writing a calculator function
Class 4: Lists, Tuples, and Dictionaries

4 lectures • 0m

Lists: Indexing, slicing, and modifying elements
Tuples and when to use them
Dictionaries: Keys, values, and looping through them
Hands-on: Creating and manipulating a student database
Class 5: File I/O and Exception Handling

4 lectures • 0m

Reading and writing files
Working with CSV and text files
Try-except blocks for handling errors
Hands-on: Reading and processing a text file
Class 6: Object-Oriented Programming (OOP)

4 lectures • 0m

Classes and objects
Attributes and methods
Inheritance and polymorphism
Hands-on: Building a simple bank account system
Class 7: Introduction to Pandas

3 lectures • 0m

DataFrames and Series
Basic operations: Filtering, sorting, modifying data
Hands-on: Loading and analyzing a small dataset
Class 8: Basic Data Visualization with Matplotlib

3 lectures • 0m

Creating simple plots: Line plots, bar charts, Customizing
Customizing plots with titles, labels, and legends
Hands-on: Visualizing trends in a dataset
AI/ML Syllabus

0 lectures • 0m

Class 9: What is Machine Learning?

3 lectures • 0m

Overview: Supervised vs. Unsupervised Learning
Understanding features and labels
Hands-on: Loading a dataset and exploring it
Class 10: First ML Models – Regression & Classification

3 lectures • 0m

Linear Regression: Training a basic model in Python
Logistic Regression for classification
Hands-on: Predicting house prices and spam detection
Class 11: Decision Trees and Random Forests

2 lectures • 0m

How decision trees work
Hands-on: Customer churn prediction
Class 12: Support Vector Machines & k-Nearest

3 lectures • 0m

SVM for classification
kNN for recommendation systems
Hands-on: Classifying images or text
Class 13: Clustering Techniques

2 lectures • 0m

K-Means and hierarchical clustering
Hands-on: Customer segmentation
Class 14: Dimensionality Reduction

2 lectures • 0m

PCA for feature reduction
Hands-on: Improving model efficiency with PCA
Class 15: Introduction to Neural Networks

2 lectures • 0m

Basics of perceptrons and activation functions
Hands-on: Building a neural network using TensorFlow
Class 16: Training Deep Learning Models

2 lectures • 0m

Loss functions, optimization techniques
Hands-on: Training an image classification model
Class 17: Image Processing with CNNs

2 lectures • 0m

Understanding convolution and pooling
Hands-on: Building an image classifier
Class 18: Using Pretrained Models

2 lectures • 0m

Transfer learning with existing models
Hands-on: Fine-tuning a model for custom tasks
Class 19: Basics of NLP

2 lectures • 0m

Tokenization, stopwords, stemming
Hands-on: Text classification
Class 20: Advanced NLP with Transformers

2 lectures • 0m

Introduction to BERT and GPT models
Hands-on: Named entity recognition
Class 21: Deploying AI Models with Flask/FastAPI

2 lectures • 0m

Creating an API endpoint for a model
Hands-on: Serving predictions via a web API
Class 22: Scaling and Optimizing Models

2 lectures • 0m

Model compression and inference optimization
Hands-on: Deploying models on AWS/GCP
Class 23: Hands-on Capstone Project

2 lectures • 0m

Students work on a real-world ML problem
Hands-on: Dataset selection and model development
Class 24: Project Presentations & Career Prep

2 lectures • 0m

Resume building, interview tips, and job search strategies
Hands-on: Mock technical interview questions

About the Instructor

Syed Nawshad

Syed Nawshad

Syed Nawshad is an accomplished Data Scientist holding a Master’s degree in AI, specializing in building secure, enterprise-grade artificial intelligence solutions. With a robust background spanning government projects and multiple Fortune 500 companies, Syed excels at architecting cutting-edge intelligent systems for mission-critical operations. He is a strategic technical partner, expert at leveraging advanced AI methodologies to solve complex data challenges and drive high-impact operational success.

5.0

Instructor rating

1,600

Students

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Courses

Student Feedback

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"AI & Machine Learning course at DFW IT Career gave me a solid foundation in artificial intelligence and machine learning. The instructors explained complex concepts using practical examples, and the hands-on projects helped me understand how AI is used in real business environments."

Christopher Lee

Christopher Lee

Verified Learner

"I was looking for an AI course that focused on practical skills instead of just theory, and this program delivered exactly that. We worked with machine learning models, data analysis, and real-world AI applications. The instructors were experienced and always willing to help."

Emily Rodriguez

Emily Rodriguez

Verified Learner

"This is one of the best AI training programs I've attended. The curriculum covers machine learning fundamentals, predictive analytics, model evaluation, and AI tools that are relevant in today's job market. The practical labs made learning much more effective."

Arjun Mehta

Arjun Mehta

Verified Learner

"The AI & Machine Learning course exceeded my expectations. Every topic was explained clearly, from supervised learning to model deployment. The hands-on exercises gave me confidence to start building my own machine learning projects."

Stephanie Nguyen

Stephanie Nguyen

Verified Learner

"Excellent course for anyone interested in starting a career in Artificial Intelligence. The instructors combined theory with real-world projects, making it easy to understand machine learning concepts and business applications. I highly recommend this training."

Faisal Ahmed

Faisal Ahmed

Verified Learner

Course Pricing

AI & Machine Learning FREE

$0 /one-time
  • Access to 2 Live Classes
  • Access to Student Portal
  • No Payment, No Commitment
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AI & Machine Learning 4 Monthly ISA

$1,000 /one-time
  • 4 Easy Monthly Payments
  • Access to Student Portal
  • Access to Live Classes
  • Access to Video Materials
  • Teamwork Collaboration Platform
  • Contractual Agreement
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Most Popular

AI & Machine Learning Full Registration

$3,500 /one-time
  • Access to all Live Classes
  • Access to Video Materials
  • Job Support
  • Access to Student Portal
  • Full Payment
  • Interview Materials
  • Contractual Agreement
  • Teamwork Collaboration Platform
  • 24/7 Mentorship
Enroll Now

Frequently Asked Questions

You'll learn Artificial Intelligence fundamentals, machine learning algorithms, supervised and unsupervised learning, predictive analytics, data preprocessing, model evaluation, feature engineering, and practical AI project development using industry-relevant tools.

Yes. The course is designed for beginners as well as IT professionals. While basic programming knowledge is helpful, the curriculum starts with core AI and machine learning concepts before moving into advanced topics.

Yes. Students work on real-world machine learning projects, practical datasets, model training, evaluation, and AI applications that help build job-ready experience.

Graduates can pursue roles such as: AI Engineer Machine Learning Engineer Data Analyst Data Scientist AI Solutions Consultant Business Intelligence Analyst AI Developer

DFW IT Career provides instructor-led training, hands-on labs, real-world AI projects, flexible online and classroom learning options, and career-focused instruction designed to prepare students for today's AI and machine learning job market.