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
Assessment:
- Weekly practical exercises and data analysis tasks
- Final project evaluation and presentation
Certification:
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
- Employers: Systems, Confiz, Afiniti
- Experience: Above six years
- Gold Medalist (Data Sciences and AI)
Mamoona Riaz
Lead, AI & ML Engineer
- Employers: Arbisoft, Datics AI and C-SALT
- Clients: edX
- Experience: Above five years
- Masters Degree (Data Sciences and AI)