Data Science & Machine Learning Bootcamp

    mediumbeginerIntermediate 8 Weaks

    Data Science & Machine Learning Bootcamp

    Instructor: NexusBerry
    NexusBerry DataScience and Machine Learning Course

    Graduation Portfolio (projects — different domains across the ML workflow)

    1. Full EDA insight report — retail/e-commerce (L4–6, pandas + Seaborn)
    2. A/B-test verdict report — marketing (L7–9, pandas + SciPy)
    3. House-price prediction pipeline — real estate (L11–12, scikit-learn Pipeline)
    4. Customer-churn classifier — telecom (L13–15, scikit-learn + XGBoost)
    5. Customer segmentation — retail (L16–17, k-means + PCA)
    6. Backtested sales forecast — retail/finance (L18, time-series features + regression)
    7. Live sentiment-analysis web appproduct reviews, flagship (L19–21, TF-IDF + neural net + Streamlit Cloud)
    8. Kaggle competition entry — student-chosen (L22, full workflow)
    9. Individual capstone — student's chosen domain & dataset, presented at Demo Day (L24)

    Tech stack: Python (NumPy, pandas, Matplotlib, Seaborn) · Jupyter / Google Colab · scikit-learn · XGBoost · SciPy · joblib · Streamlit + Streamlit Community Cloud · ChatGPT / Claude as AI pair-analyst · Kaggle (datasets & competitions) · GitHub portfolio · real datasets from retail/e-commerce, telecom, real estate, finance & marketing (Pakistan-relevant where possible)

    Description

    Explore the foundations of Data Science, Machine Learning, and Artificial Intelligence through practical Python programming and real-world datasets. Learn data analysis with Pandas, data visualization, feature engineering, machine learning using Scikit-learn, model evaluation, and predictive analytics while completing hands-on projects. This bootcamp provides a solid pathway into modern AI and data science, preparing learners for advanced machine learning, deep learning, and AI engineering studies.

    Why Choose Our AI Data Science and Machine Learning Training Bootcamp?

    • Hands-on Experience: Gain practical, real-world experience through hands-on projects and case studies, equipping you with the skills to tackle complex data challenges confidently.
    • Expert Instructors: Learn from industry experts with extensive experience in data science and machine learning, who will guide you every step of the way and share their invaluable insights.
    • Comprehensive Curriculum: Our meticulously designed curriculum covers a wide range of topics, including Advance Python programming for DSML, applied statistics, data analysis and visualization, supervised and unsupervised learning algorithms, reinforcement learning, artificial neural networks and many more topics.
    • Practical Applications: Explore diverse applications of data science, such as personalized customer experiences, fraud detection, optimized marketing strategies, and efficient resource allocation.
    • Industry-Relevant Skills: Acquire in-demand skills that are highly sought after by employers in today's data-driven world, positioning yourself for exciting career opportunities and advancement.
    • Flexible Learning Options: Our flexible learning options allow you to choose between: online or physical, weekdays or weekends, standard or fast-track. Learn as per your convenience.

    Labs Index (16 TA-led practice sessions · 2 per week)

    LabWkFocus
    11Toolkit setup clinic (Colab/Anaconda/GitHub); NumPy drills
    21pandas first-steps drill set (loading, selecting, filtering)
    32Data-cleaning clinic on messy datasets
    42groupby/merge challenge + EDA gallery build
    53Statistics practice: distributions & confidence intervals by simulation
    63A/B-testing workshop on campaign data
    74First-models clinic: KNN & regression on fresh datasets
    84Pipeline & feature-engineering practice; Phase-2 project support
    95Classification-metrics drills; imbalanced-data practice
    105Ensemble & tuning challenge (mini leaderboard, Kaggle-style)
    116Segmentation build-along + PCA practice
    126Forecasting clinic on sales data
    137NLP practice; capstone kickoff & scoping
    147Neural-net experiments; Streamlit deployment clinic
    158Capstone build clinic; Kaggle submission support
    168Demo-day rehearsal; portfolio, CV & freelance-profile clinic

    Course Outline

    Instructor

    Instructor Picture

    NexusBerry

    Instructor

    Data Science & Machine Learning Bootcamp with NexusBerry

    • beginermedium
    • 8 Weeks
    • 24 Lessons
    • 9 Projects
    • Instructor: nexusberry
    • NexusBerry Training & Solutions

    Get in touch with the NexusBerry team to schedule your Free Demo Session or learn more about our upcoming training batches