The Advanced Big Data Analysis Using R and Python course is designed for data professionals, analysts, and researchers looking to enhance their expertise in big data analytics. This intensive training provides hands-on experience with data manipulation, statistical modelling, machine learning, and AI-driven insights using R and Python—two of the most powerful programming languages for data science.
Participants will gain proficiency in real-time data processing, advanced analytics techniques, and cloud-based big data solutions, ensuring they stay ahead in the fast-evolving world of data science.
Course Objectives
By the end of this course, participants will:
✔ Master advanced big data processing and analysis using R and Python.
✔ Develop expertise in data visualization, statistical modeling, and machine learning.
✔ Utilize big data frameworks such as Hadoop, Spark, and cloud computing tools.
✔ Implement predictive analytics and AI-driven insights for decision-making.
✔ Optimize real-time data processing for business intelligence and forecasting.
✔ Ensure data integrity, security, and compliance with global standards.
✔ Apply automation, deep learning, and advanced AI techniques for scalable analytics.
Course Modules
- Introduction to Big Data Analytics
- Understanding big data applications across industries.
- Overview of R and Python for data analysis.
- Key tools & libraries: NumPy, Pandas, ggplot2, dplyr, Scikit-learn, TensorFlow.
- Data Manipulation and Cleaning
- Importing, processing, and transforming large datasets.
- Handling missing data, outliers, and normalization techniques.
- Data wrangling using dplyr (R) and Pandas (Python).
- Statistical Analysis and Machine Learning
- Advanced statistical modeling (ANOVA, regression, hypothesis testing).
- Supervised & unsupervised learning: classification, clustering, and predictive modeling.
- Feature selection, dimensionality reduction, and model evaluation.
- Big Data Processing with Hadoop and Spark
- Introduction to Hadoop ecosystem (HDFS, MapReduce, Hive).
- Real-time data processing with Apache Spark.
- Scalable machine learning using MLlib and PySpark.
- AI and Deep Learning in Data Science
- Deep learning frameworks: TensorFlow & Keras.
- Neural networks, CNNs, RNNs, and NLP applications.
- Automating machine learning (AutoML) for business intelligence.
- Data Visualization and Reporting
- Creating interactive dashboards with R Shiny and Plotly.
- Advanced visualization with ggplot2, Matplotlib, and Seaborn.
- Real-time data storytelling for decision-making.
- Cloud Computing and Scalable Big Data Solutions
- Cloud-based analytics with AWS, Azure, and Google Cloud.
- Distributed computing and storage solutions.
- Implementing serverless architectures for scalable big data processing.
Target Audience
This course is ideal for professionals in:
✔ Data Science & Analytics – Data Scientists, Analysts, Business Intelligence Experts.
✔ Software Development & IT – Developers, IT Professionals, Cloud Engineers.
✔ Finance & Banking – Risk Analysts, Quantitative Researchers, Financial Data Analysts.
✔ Healthcare & Research – Clinical Data Analysts, Bioinformatics Professionals.
✔ Marketing & E-commerce – Digital Marketers, Consumer Data Analysts, Market Researchers.
✔ Academia & Research – University Lecturers, Postgraduate Students, AI Researchers.
Industries That Benefit from This Course
✔ Banking & Finance – Fraud detection, algorithmic trading, risk management.
✔ Healthcare & Pharmaceuticals – Predictive analytics, disease modeling, genomics research.
✔ Retail & E-commerce – Customer segmentation, recommendation systems, demand forecasting.
✔ Telecommunications – Network optimization, churn prediction, customer analytics.
✔ Energy & Utilities – Smart grid analytics, predictive maintenance, energy consumption forecasting.
✔ Government & Public Sector – Policy optimization, census analytics, fraud detection.
✔ Agriculture & Environmental Science – Climate modeling, crop yield predictions, remote sensing.
General Information
Customized Training Options
✔ Tailored Learning Paths – Course content adapted to industry needs.
✔ English Proficiency Required – Instruction delivered in English.
✔ Engaging Learning Methods – Interactive presentations, coding exercises, and case studies.
✔ Globally Recognized Certification – Earn an industry-recognized certification.
✔ Flexible Training Locations – Attend in-person at STRI centers, in-house, or online.
✔ Adjustable Course Duration – Customized based on participants’ needs.
Training Package Includes:
✔ Expert-led sessions and world-class training materials.
✔ Hands-on projects and access to real-world datasets.
✔ Certification upon successful course completion.
✔ Networking opportunities with industry professionals.
✔ Refreshments (for in-person sessions) and technical support.
Additional Services:
✔ Affordable accommodation options & airport pickup services.
✔ Visa assistance available for international participants.
✔ Laptops & software tools available for rent.
✔ Six months of post-training support (mentorship & coaching).
Group Discounts & Payment Plans:
✔ Discounts for groups of four or more.
✔ Flexible payment options (full payment before training or per agreement).
Enroll Today!
📞 Call/WhatsApp: +254 723 482 495 | +254 757 155 287
📧 Email: info@stepsureresearchinstitute.org
🌍 Website: www.stepsureresearchinstitute.org
