+44 7459 302492
support@uplatz.com
( 795 Students )
Project on Data Science Implementation with Python
Master Real-World Data Science Applications with Python Through Hands-On Projects – From Data Cleaning to Predictive Modeling
View Course Curriculum
Price Match Guarantee
Full Lifetime Access
Access on any Device
Technical Support
Secure Checkout
Course Completion Certificate
95% Started a new career
BUY THIS COURSE (USD 12 USD 41 )-
96% Got a pay increase and promotion
Students also bought -
-
- Data Science with R
- 25 Hours
- USD 12
- 479 Learners
-
- Artificial Intelligence, Data Science, and Machine Learning with Python
- 52 Hours
- USD 12
- 5867 Learners
-
- Career Accelerator - Head of Data, Analytics, and Machine Learning
- 200 Hours
- USD 45
- 650 Learners
Project on Data Science Implementation with Python is a self-paced – Online Course
Project on Data Science Implementation with Python is a self-paced, hands-on online training program designed for aspiring and early-career data scientists who want to go beyond theory and apply their skills in real-world scenarios. Through this practical, project-based course, learners gain essential experience by working on an end-to-end implementation of a Loan Prediction Project, one of the most relevant and common applications in the financial services industry.
This course is not just about learning Python or understanding data science concepts in isolation. Instead, it focuses on integrating data science workflows into a coherent, project-driven structure that mirrors the actual job responsibilities of a data scientist. From data cleaning and preprocessing to exploratory data analysis (EDA), feature engineering, model training, hyperparameter tuning, and evaluation, each phase is covered thoroughly with expert guidance.
Delivered through high-quality pre-recorded video sessions, the course allows you to learn at your own pace and revisit concepts anytime. You’ll learn how to write clean, efficient code, visualize insights, and build predictive models using Python's most powerful libraries, including pandas, NumPy, matplotlib, seaborn, scikit-learn, and more.
On successful completion, you will receive a Course Completion Certificate, which you can showcase on your resume, LinkedIn profile, or professional portfolio to highlight your applied data science capabilities.
Why This Course Stands Out
While many data science courses are heavy on theory and light on real-world context, this program flips the script. It focuses on implementation—a crucial skill set hiring managers are looking for today. By guiding you through a real project from start to finish, this course builds the kind of confidence and competence that only comes from practical experience.
You will not only learn how data science models work, but more importantly, you'll understand how to apply them to solve meaningful business problems, communicate results effectively, and prepare your code and findings for production-level deployment.
The central case study—a loan default prediction project—represents a classic machine learning application with real-life stakes. It provides the ideal framework to practice key concepts like data preprocessing, handling missing values, outlier detection, statistical insights, categorical encoding, model selection, and performance metrics such as accuracy, precision, recall, F1-score, and ROC-AUC.
Whether you're preparing for a data science job, aiming to transition from another role, or seeking to sharpen your implementation skills, this course offers the right balance of depth, practicality, and flexibility.
Who Should Take This Course
This course is ideal for:
- Aspiring data scientists or machine learning engineers looking to build practical experience
- Python programmers who want to specialize in data science and analytics
- Graduates or students with a theoretical background in data science or statistics, seeking hands-on exposure
- Working professionals transitioning into analytics or data science roles
- Anyone preparing for technical interviews where real-world project experience is a strong differentiator
Whether you’re just starting out or brushing up on project-level skills, this course gives you the structure and content you need to succeed.
How to Use This Course
To make the most of your learning experience, follow these recommended steps for navigating and engaging with the course content:
1. Set Up Your Environment First
Before diving into the videos, set up your local Python environment using tools such as Anaconda, Jupyter Notebook, or VS Code. The course walks you through the tools you'll need, but having everything ready ahead of time will help you code along seamlessly.
2. Follow the Videos Step-by-Step
Watch the video sessions in order, as each step builds upon the last. Pause frequently, take notes, and be sure to code along with the instructor. Hands-on practice is key to solidifying your understanding.
3. Replicate and Experiment with the Code
Don’t just replicate what’s in the video—experiment. Change parameters, add new features, tweak models, and test different strategies. This experimentation helps transform passive watching into active learning.
4. Use Real-Time Documentation
As you go through the modules, keep the official documentation for libraries like pandas, matplotlib, and scikit-learn open in a browser tab. This habit not only helps clarify concepts but also builds good practices for real-world problem-solving.
5. Pause and Reflect on Each Phase
After each major section—EDA, preprocessing, model training, etc.—take time to reflect. Ask yourself:
- What was the goal of this phase?
- What tools did I use and why?
- How would I explain this step to a colleague or interviewer?
These reflections deepen your comprehension and prepare you for communicating your results clearly.
6. Document Your Work
As you build the project, maintain your own version of the Jupyter Notebook with detailed comments and markdown explanations. This becomes a valuable artifact for interviews, presentations, or GitHub portfolios.
7. Explore Additional Datasets
Once you finish the core loan prediction project, try applying the same workflow to a different dataset (e.g., from Kaggle or UCI Machine Learning Repository). This extends your learning and builds confidence in tackling new problems.
8. Ask Questions and Engage in Communities
Although the course is self-paced, you can enhance your learning by engaging in online forums like Stack Overflow, GitHub Discussions, or data science communities on LinkedIn and Reddit. Share your project, ask for feedback, or explore how others approach similar problems.
9. Review Key Concepts Before Interviews
If you’re preparing for job interviews, revisit key modules such as data cleaning, feature selection, and model evaluation. Be prepared to explain your workflow, reasoning, and results—this course gives you all the foundation you need.
What You Will Achieve
By the end of this course, you will:
- Complete a full-cycle machine learning project using real-world data
- Gain practical experience in data preparation, visualization, modeling, and evaluation
- Understand how to handle common issues like missing data, categorical variables, and imbalanced datasets
- Be able to apply Python-based tools and libraries to solve predictive modeling problems
- Build a personal project portfolio to showcase your data science capabilities
- Be well-prepared for technical interviews and real-world job roles
- Receive a Course Completion Certificate that validates your practical expertise
This is not just a course—it’s a launchpad for your data science journey, designed to bridge the gap between theory and application in the most effective way possible.
By the end of this course, learners will be able to:
- Understand the End-to-End Data Science Workflow – From problem definition to model deployment.
- Apply Data Cleaning Techniques – Handle missing values, outliers, and inconsistencies in datasets.
- Perform Exploratory Data Analysis (EDA) – Visualize data distributions, correlations, and patterns.
- Engineer Features for Better Predictions – Transform raw data into meaningful features.
- Build and Train Machine Learning Models – Implement algorithms like Logistic Regression, Decision Trees, and Random Forests.
- Evaluate Model Performance – Use metrics like accuracy, precision, recall, and ROC-AUC.
- Interpret Results for Decision-Making – Translate model outputs into actionable insights.
- Deploy a Simple Predictive Model – Learn basics of model deployment using Flask or Streamlit.
- Document and Present Findings – Create a professional project report and presentation.
Lecture 1: Introduction to Loan Prediction Project
- Problem statement and business context
- Dataset overview and initial exploration
- Setting up the Python environment (Jupyter, Pandas, NumPy)
Lecture 2: Data Cleaning and Preprocessing
- Handling missing values and outliers
- Categorical data encoding (One-Hot, Label Encoding)
- Feature scaling and normalization
Lecture 3: Exploratory Data Analysis (EDA) and Visualization
- Univariate and bivariate analysis
- Correlation matrices and heatmaps
- Visualizations using Matplotlib and Seaborn
Lecture 4: Feature Engineering and Selection
- Creating new features (e.g., debt-to-income ratio)
- Feature importance analysis
- Dimensionality reduction (PCA, if applicable)
Lecture 5: Model Building and Evaluation
- Splitting data into train/test sets
- Implementing algorithms (Logistic Regression, Decision Trees, Random Forests)
- Hyperparameter tuning (GridSearchCV)
- Performance metrics and confusion matrices
Upon successful completion of the Project on Data Science Implementation with Python course, learners will receive a Course Completion Certificate from Uplatz, validating their hands-on skills in data science and Python programming. This certification demonstrates your ability to tackle real-world data problems, from data wrangling to predictive modeling, making you a competitive candidate for roles in data science, analytics, and AI.
Completing this course opens doors to various roles in the data-driven industry, including:
- Data Scientist
- Machine Learning Engineer
- Data Analyst
- Business Intelligence Analyst
- AI Research Assistant
Industries like finance, healthcare, e-commerce, and marketing actively seek professionals with hands-on data science skills.
- How did you approach data cleaning in your loan prediction project?
I began by identifying missing values, outliers, and inconsistencies in the dataset. For missing data, I used techniques like mean/median imputation for numerical features and mode imputation for categorical ones. Outliers were handled using IQR (Interquartile Range) or domain-specific thresholds. I also standardized formats (e.g., date columns) and removed duplicates to ensure data integrity. - What feature engineering techniques did you apply, and why?
I created new features such as debt-to-income ratio (Total Debt / Income) to capture financial health, and loan-to-value ratio (Loan Amount / Asset Value) for risk assessment. Categorical variables like employment type were encoded using One-Hot Encoding to preserve meaning. Feature scaling (StandardScaler) was applied to normalize numerical features for model stability. - How did you select the best model for your loan prediction problem?
I tested multiple algorithms (Logistic Regression, Decision Trees, Random Forests) and compared their performance using metrics like accuracy, precision, recall, and ROC-AUC. Random Forest performed best due to its ability to handle non-linear relationships and feature importance insights. Hyperparameter tuning (GridSearchCV) further optimized the model.
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.