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Artificial Intelligence, Data Science, and Machine Learning with Python

Build Real-World AI, Data Science, Machine Learning Solutions with Python: From Data Wrangling & Visualization to Predictive Modeling, Deep Learning.
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Course Duration: 52 Hours
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Artificial Intelligence, Data Science & Machine Learning with Python | Self-Paced Online Course

Unlock your potential and advance your career in the cutting-edge domains of Artificial Intelligence (AI), Data Science, and Machine Learning (ML) through this expertly curated self-paced online course. Designed with a strong focus on Python—the most widely used language in data-driven technologies—this course is your gateway to mastering the skills that power the future of intelligent systems and data-driven decision-making.

This course is more than just an academic introduction; it's a practical, hands-on journey into the real-world applications of AI, ML, and Data Science using Python. Whether you're aiming to become a data scientist, machine learning engineer, AI developer, or a technical analyst, this course is crafted to provide a strong and adaptable foundation. It delivers not only theoretical understanding but also applicable coding skills and problem-solving techniques that are in high demand across industries.

Python serves as the backbone of this course, and for good reason. It has become the go-to programming language for AI and Data Science due to its simplicity, readability, and expansive ecosystem of libraries and frameworks. In this course, you'll work with essential Python libraries such as:

  • NumPy and Pandas for data manipulation and analysis
  • Matplotlib and Seaborn for data visualization
  • Scikit-learn for machine learning algorithms
  • TensorFlow and PyTorch for deep learning and neural networks
  • NLTK and spaCy for natural language processing

From the ground up, you'll learn how to import and clean datasets, perform exploratory data analysis, visualize insights, and build predictive models. The course covers both supervised and unsupervised learning techniques, enabling you to solve classification, regression, clustering, and dimensionality reduction problems with confidence. As you progress, you’ll also explore advanced topics such as deep learning, reinforcement learning, and AI-driven automation systems.

What truly sets this course apart is its project-based structure. Real-world projects and coding exercises accompany each module to reinforce the concepts and enhance practical understanding. These projects mirror actual industry scenarios, giving you a chance to apply your knowledge in tasks such as fraud detection, sentiment analysis, image classification, recommendation systems, and predictive analytics. By the end of the course, you'll have a portfolio of completed projects that demonstrate your ability to solve real business challenges using AI and data science techniques.

How to Use This Course Effectively

This self-paced course is designed for maximum flexibility, allowing you to learn at your own speed while still gaining comprehensive, industry-relevant skills. Here's how you can make the most out of this learning experience:

  1. Start with the Basics
    If you're new to Python or programming, begin with the foundational modules that introduce Python syntax, variables, data types, and control flow. These lessons will build the groundwork for more advanced topics.
  2. Follow a Structured Path
    Though the course is self-paced, it follows a logical progression—from basic data handling to complex machine learning and AI models. It’s highly recommended to complete the modules in order to avoid missing key concepts that build upon one another.
  3. Engage with the Videos and Hands-On Exercises
    Each video tutorial is complemented by interactive coding labs and practical exercises. Try to code along with the instructor and attempt each problem on your own to reinforce your learning. Rewatch sections as needed to clarify doubts.
  4. Work on the Projects Seriously
    Treat the real-world projects as mini-internships. They are designed to simulate professional tasks and are essential for applying theoretical knowledge. Document your work thoroughly, as these can serve as portfolio pieces for future job applications or interviews.
  5. Use External Resources for Deeper Learning
    While the course content is comprehensive, you may benefit from supplemental materials such as documentation, research papers, GitHub repositories, and forums like Stack Overflow. Don’t hesitate to explore these as you dive deeper into complex topics.
  6. Practice Regularly and Revisit Concepts
    Machine Learning and AI are not just about understanding theory—they require continuous practice. Regularly revisit earlier modules to keep your skills sharp. Practice coding on your own and try to replicate models using different datasets.
  7. Test Your Knowledge Frequently
    Use the built-in quizzes and assessments to test your understanding of each topic. These will help reinforce what you’ve learned and identify areas that may need more focus.
  8. Stay Curious and Explore
    AI and Data Science are evolving fields. After completing the course, continue experimenting with new datasets, trying out different algorithms, and exploring new tools and libraries. The knowledge you gain here will be your stepping stone into more advanced studies or professional roles.
  9. Build a Network and Share Your Work
    Share your completed projects on GitHub, LinkedIn, or Kaggle. Join online communities of learners and professionals. Networking not only enhances your learning but also opens doors to collaboration and career opportunities.

Who Should Take This Course?

This course is ideal for:

  • Beginners who want to enter the fields of Data Science, AI, or ML
  • Working professionals looking to pivot into tech or upskill for better opportunities
  • Engineers and developers aiming to integrate AI features into their applications
  • Analysts and statisticians seeking to enhance their technical and programming proficiency

By the end of this course, you will have the skills, confidence, and hands-on experience needed to tackle real-world AI and data science problems using Python. Whether your goal is academic enrichment, personal development, or professional advancement, this course empowers you to take the next big step in your tech journey.

Course Objectives Back to Top

By the end of this course, learners will be able to:

  1. Understand the fundamentals of AI, data science, and machine learning.
  2. Work with Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, and Keras.
  3. Perform data preprocessing, data cleaning, and exploratory data analysis (EDA).
  4. Build and evaluate machine learning models including regression, classification, and clustering.
  5. Implement deep learning models using neural networks and TensorFlow/Keras.
    Apply Natural Language Processing (NLP) for text classification, sentiment analysis, and chatbot development.
  6. Develop AI projects such as image recognition, recommendation systems, and prediction engines.
  7. Work on real-world datasets from healthcare, finance, e-commerce, and more.
  8. Understand model deployment, API creation with Flask, and model performance monitoring.
  9. Prepare for roles in data science, AI development, and machine learning engineering.
Course Syllabus Back to Top

Course Curriculum: Artificial Intelligence, Data Science & Machine Learning with Python

Master the essential skills in AI, Data Science, and Machine Learning with hands-on Python training. This comprehensive course covers everything from Python programming to advanced ML algorithms, ensuring you gain practical expertise for real-world applications.

Course Modules

1. Introduction to AI, Data Science & Python Setup

  • Overview of AI and Data Science
  • Key components and industry applications
  • Setting up Python with Anaconda, Jupyter Notebook, and Spyder IDE

2. Python Programming Fundamentals

  • Variables, operators, and data structures (lists, tuples, dictionaries)
  • Control flow (loops, conditionals, functions)
  • Lambda functions, recursion, and error handling

3. Data Importing & Cleaning

  • Importing data from CSV, Excel, SQL, APIs, and web scraping
  • Handling missing values, outliers, and inconsistencies
  • Data manipulation with NumPy & Pandas

4. Exploratory Data Analysis (EDA) & Statistics

  • Descriptive statistics (mean, median, variance, skewness)
  • Univariate, bivariate, and multivariate analysis
  • Probability distributions (Normal, Binomial, Poisson)

5. Data Visualization

  • Creating plots with Matplotlib & Seaborn (histograms, scatter plots, box plots)
  • Interactive visualizations with Plotly
  • Storytelling with data

6. Statistical Inference & Hypothesis Testing

  • Confidence intervals, p-values, and Z/T-tests
  • ANOVA, Chi-square tests, correlation analysis
  • Bayesian probability & sampling techniques

7. Machine Learning & Predictive Modeling

Supervised Learning:

  • Regression (Linear, Polynomial, Logistic)
  • Classification (Decision Trees, SVM, KNN, Naive Bayes)

Unsupervised Learning:

  • Clustering (K-Means, Hierarchical, DBSCAN)
  • Dimensionality Reduction (PCA, LDA)
  • Ensemble Methods (Random Forest, Boosting, Bagging)

8. Capstone Project

  • End-to-end real-world project applying all concepts
  • Problem-solving with AI/ML pipelines
  • Model deployment insights
Certification Back to Top

Upon successfully completing the Artificial Intelligence, Data Science, and Machine Learning with Python course, learners will receive a Course Completion Certificate from Uplatz, validating their expertise in building AI and ML models using Python.
This certificate strengthens your professional profile and supports career growth in data science, AI engineering, machine learning, and advanced analytics.

Career & Jobs Back to Top

With the demand for AI and data science professionals growing rapidly, completing this course will position you for roles in top organizations across industries like finance, healthcare, e-commerce, and technology. Career paths include:

  1. Data Scientist
  2. Machine Learning Engineer
  3. AI Developer
  4. Data Analyst
  5. Python Developer
  6. Deep Learning Specialist
  7. Business Intelligence Analyst

Professionals with strong Python-based AI and data skills are essential to companies aiming to build smart, data-driven solutions.

Interview Questions Back to Top

1. What is the difference between AI, machine learning, and data science?
AI focuses on creating intelligent systems, ML is a subset that involves algorithms learning from data, and data science includes data analysis, visualization, and model building.

2. Why is Python used in AI and data science?
Python offers simplicity, readability, and powerful libraries like Pandas, NumPy, and TensorFlow, making it ideal for AI, ML, and data analysis tasks.

3. What is supervised vs. unsupervised learning?
Supervised learning uses labeled data to train models (e.g., regression, classification), while unsupervised learning finds hidden patterns in unlabeled data (e.g., clustering).

4. What is overfitting and how can it be prevented?Overfitting occurs when a model performs well on training data but poorly on new data. It can be reduced using cross-validation, regularization, or pruning.

5. What is a confusion matrix?
It’s a table that evaluates classification models by showing the true vs. predicted values across categories, helping measure accuracy, precision, recall, and F1 score.

6. How does a neural network work?
Neural networks simulate the human brain, with layers of nodes (neurons) connected by weights that adjust during training to recognize complex patterns.

7. What is TensorFlow used for?
TensorFlow is an open-source framework used to build and deploy deep learning and machine learning models efficiently.

8. What are the steps in a data science project?
Data collection, cleaning, exploration, feature engineering, model building, evaluation, and deployment.

9. What is cross-validation?
A technique for assessing model performance by dividing the data into multiple training and testing sets to ensure generalization.

10. How do you deploy a machine learning model?
You can deploy using Flask or FastAPI to expose the model via an API, or use cloud platforms like AWS SageMaker, Azure ML, or GCP AI Platform.

Course Quiz Back to Top
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Q1. What are the payment options? A1. We have multiple payment options: 1) Book your course on our webiste by clicking on Buy this course button on top right of this course page 2) Pay via Invoice using any credit or debit card 3) Pay to our UK or India bank account 4) If your HR or employer is making the payment, then we can send them an invoice to pay. Q2. Will I get certificate? A2. Yes, you will receive course completion certificate from Uplatz confirming that you have completed this course with Uplatz. Once you complete your learning please submit this for to request for your certificate https://training.uplatz.com/certificate-request.php Q3. How long is the course access? A3. All our video courses comes with lifetime access. Once you purchase a video course with Uplatz you have lifetime access to the course i.e. forever. You can access your course any time via our website and/or mobile app and learn at your own convenience. Q4. Are the videos downloadable? A4. Video courses cannot be downloaded, but you have lifetime access to any video course you purchase on our website. You will be able to play the videos on our our website and mobile app. Q5. Do you take exam? Do I need to pass exam? How to book exam? A5. We do not take exam as part of the our training programs whether it is video course or live online class. These courses are professional courses and are offered to upskill and move on in the career ladder. However if there is an associated exam to the subject you are learning with us then you need to contact the relevant examination authority for booking your exam. Q6. Can I get study material with the course? A6. The study material might or might not be available for this course. Please note that though we strive to provide you the best materials but we cannot guarantee the exact study material that is mentioned anywhere within the lecture videos. Please submit study material request using the form https://training.uplatz.com/study-material-request.php Q7. What is your refund policy? A7. Please refer to our Refund policy mentioned on our website, here is the link to Uplatz refund policy https://training.uplatz.com/refund-and-cancellation-policy.php Q8. Do you provide any discounts? A8. We run promotions and discounts from time to time, we suggest you to register on our website so you can receive our emails related to promotions and offers. Q9. What are overview courses? A9. Overview courses are 1-2 hours short to help you decide if you want to go for the full course on that particular subject. Uplatz overview courses are either free or minimally charged such as GBP 1 / USD 2 / EUR 2 / INR 100 Q10. What are individual courses? A10. Individual courses are simply our video courses available on Uplatz website and app across more than 300 technologies. Each course varies in duration from 5 hours uptop 150 hours. Check all our courses here https://training.uplatz.com/online-it-courses.php?search=individual Q11. What are bundle courses? A11. Bundle courses offered by Uplatz are combo of 2 or more video courses. We have Bundle up the similar technologies together in Bundles so offer you better value in pricing and give you an enhaced learning experience. Check all Bundle courses here https://training.uplatz.com/online-it-courses.php?search=bundle Q12. What are Career Path programs? A12. Career Path programs are our comprehensive learning package of video course. These are combined in a way by keeping in mind the career you would like to aim after doing career path program. Career path programs ranges from 100 hours to 600 hours and covers wide variety of courses for you to become an expert on those technologies. Check all Career Path Programs here https://training.uplatz.com/online-it-courses.php?career_path_courses=done Q13. What are Learning Path programs? A13. Learning Path programs are dedicated courses designed by SAP professionals to start and enhance their career in an SAP domain. It covers from basic to advance level of all courses across each business function. These programs are available across SAP finance, SAP Logistics, SAP HR, SAP succcessfactors, SAP Technical, SAP Sales, SAP S/4HANA and many more Check all Learning path here https://training.uplatz.com/online-it-courses.php?learning_path_courses=done Q14. What are Premium Career tracks? A14. Premium Career tracks are programs consisting of video courses that lead to skills required by C-suite executives such as CEO, CTO, CFO, and so on. These programs will help you gain knowledge and acumen to become a senior management executive. Q15. How unlimited subscription works? A15. Uplatz offers 2 types of unlimited subscription, Monthly and Yearly. Our monthly subscription give you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews each month. Minimum committment is for 1 year, you can cancel anytime after 1 year of enrolment. Our yearly subscription gives you unlimited access to our more than 300 video courses with 6000 hours of learning content. The plan renews every year. Minimum committment is for 1 year, you can cancel the plan anytime after 1 year. Check our monthly and yearly subscription here https://training.uplatz.com/online-it-courses.php?search=subscription Q16. Do you provide software access with video course? A16. Software access can be purchased seperately at an additional cost. The cost varies from course to course but is generally in between GBP 20 to GBP 40 per month. Q17. Does your course guarantee a job? A17. Our course is designed to provide you with a solid foundation in the subject and equip you with valuable skills. While the course is a significant step toward your career goals, its important to note that the job market can vary, and some positions might require additional certifications or experience. Remember that the job landscape is constantly evolving. We encourage you to continue learning and stay updated on industry trends even after completing the course. Many successful professionals combine formal education with ongoing self-improvement to excel in their careers. We are here to support you in your journey! Q18. Do you provide placement services? A18. While our course is designed to provide you with a comprehensive understanding of the subject, we currently do not offer placement services as part of the course package. Our main focus is on delivering high-quality education and equipping you with essential skills in this field. However, we understand that finding job opportunities is a crucial aspect of your career journey. We recommend exploring various avenues to enhance your job search: a) Career Counseling: Seek guidance from career counselors who can provide personalized advice and help you tailor your job search strategy. b) Networking: Attend industry events, workshops, and conferences to build connections with professionals in your field. Networking can often lead to job referrals and valuable insights. c) Online Professional Network: Leverage platforms like LinkedIn, a reputable online professional network, to explore job opportunities that resonate with your skills and interests. d) Online Job Platforms: Investigate prominent online job platforms in your region and submit applications for suitable positions considering both your prior experience and the newly acquired knowledge. e.g in UK the major job platforms are Reed, Indeed, CV library, Total Jobs, Linkedin. While we may not offer placement services, we are here to support you in other ways. If you have any questions about the industry, job search strategies, or interview preparation, please dont hesitate to reach out. Remember that taking an active role in your job search process can lead to valuable experiences and opportunities. Q19. How do I enrol in Uplatz video courses? A19. To enroll, click on "Buy This Course," You will see this option at the top of the page. a) Choose your payment method. b) Stripe for any Credit or debit card from anywhere in the world. c) PayPal for payments via PayPal account. d) Choose PayUmoney if you are based in India. e) Start learning: After payment, your course will be added to your profile in the student dashboard under "Video Courses". Q20. How do I access my course after payment? A20. Once you have made the payment on our website, you can access your course by clicking on the "My Courses" option in the main menu or by navigating to your profile, then the student dashboard, and finally selecting "Video Courses". Q21. Can I get help from a tutor if I have doubts while learning from a video course? A21. Tutor support is not available for our video course. If you believe you require assistance from a tutor, we recommend considering our live class option. Please contact our team for the most up-to-date availability. The pricing for live classes typically begins at USD 999 and may vary.




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