3 Months (Weekends Only)

Data Sciences (Data Analytics)

This comprehensive course provides in-depth knowledge of data analytics, focusing on various techniques and tools to extract valuable insights from data. Led by seasoned professional software engineers, participants will gain hands-on experience, theoretical knowledge, and practical skills required to become proficient data analysts. The course includes practical exercises, data analysis projects, and a Live Project throughout the training plan.
  •  Understanding the role of data analytics
  •  Importance of data-driven decision making
  •  Setting up the data analytics environment
  •  Introduction to data analytics tools (e.g., Python, R)
  •  Data collection techniques (e.g., web scraping, APIs)
  •  Data cleaning and preprocessing
  •  Handling missing data and outliers
  •  Hands-on: Data preprocessing with Python
  •  EDA techniques and data visualization
  •  Statistical analysis and summary statistics
  •  Data visualization libraries (e.g., Matplotlib, Seaborn)
  •  Hands-on: EDA with real-world datasets
  •  Introduction to data mining techniques
  •  Clustering and classification algorithms
  •  Association rule mining
  •  Hands-on: Applying data mining algorithms
  •  Supervised and unsupervised learning
  •  Regression and classification algorithms
  •  Model evaluation and validation
  •  Hands-on: Building predictive models with Python
  •  Understanding time series data
  •  Time series decomposition and forecasting
  •  Hands-on: Time series analysis with real data
  •  Advanced data visualization techniques
  •  Interactive dashboards with tools like Tableau or Power BI
  •  Storytelling with data
  •  Hands-on: Creating advanced data visualizations
  •  Text preprocessing and tokenization
  •  Sentiment analysis techniques
  •  Natural Language Processing (NLP)
  •  Hands-on: Analyzing text data and sentiment
  •  Introduction to big data and Hadoop
  •  Processing and analyzing big data with Spark
  •  Hands-on: Big data analytics with Spark
  •  Role of data analytics in business decisions
  •  Data-driven strategies and case studies
  •  Ethics and privacy in data analytics
  •  Hands-on: Applying data analytics in real business scenarios
  •  Introduction to data analytics platforms (e.g., Databricks)
  •  Cloud-based data analytics services (e.g., AWS, Azure)
  •  Hands-on: Exploring data analytics platforms
  •  Project kick-off and problem definition
  •  Data collection and preprocessing for the Live Project
  •  Applying data analytics techniques to solve a real problem
  •  Report generation and presentation of findings
  •  Project presentation and demonstration
  •  Graduation and certificate distribution


  •  Weekly practical exercises and data analysis tasks
  •  Final project evaluation and presentation


Upon successful completion of the course and the Live Project, participants will receive a certificate in “Data Sciences (Data Analytics)” from “Industry Professionals.”

This course outline offers a comprehensive and hands-on approach to data analytics, guided by experienced industry professionals, and emphasizes practical skills through exercises, data analysis projects, and a Live Project throughout the three-month program. Students will gain both theoretical knowledge and practical experience in data analytics and its applications.

Fee: 39,999​

(can be paid in three equal installments plan)

Ateequa Yaqoob

Lead, Data Scientist & AI Engineer

Mamoona Riaz

Lead, AI & ML Engineer