| Course Level: | Beginner to Advanced |
| Course Duration: | 1 to 3 Months | Approximately |
| Training Days: | Flexible Schedule (Monday-Friday) |
| Training Time: | 1 Session / Day (45min-1hr) |
| Course Mode: | Dedicated Virtual class (Online) |
| Course Type: | Skill Oriented Customised Training |
| Course Start On: | On Registration | Within 5 working days |
| Class Size: | 1 to 1 | No Groups | No Batch |
Understanding the role and importance of data analytics
Exploring different types of data (structured, unstructured, semi-structured)
Overview of the data analytics process
Ethical considerations in data analytics
The Data Analytics (DA) Training Course is designed to equip participants with the knowledge and skills required to analyze and interpret data effectively. This comprehensive course covers various concepts, techniques, and tools used in data analytics, enabling participants to gain valuable insights from complex datasets. The training focuses on both theoretical foundations and practical applications to ensure participants develop a solid understanding of data analytics and its real-world implementations.
Techniques for data collection (surveys, web scraping, APIs, etc.)
Data quality assessment and data cleaning procedures
Handling missing data and outliers
Data transformation and normalization
Introduction to EDA and its objectives
Descriptive statistics and data visualization techniques
Analyzing data distributions, correlations, and trends
Identifying patterns and anomalies in data
Probability theory and its applications in data analytics
Hypothesis testing and confidence intervals
Parametric and non-parametric statistical tests
Regression analysis and predictive modeling
Principles of effective data visualization
Using tools like Tableau, Power BI, or Python libraries for visualization
Designing interactive dashboards and reports
Communicating insights through visual storytelling
Introduction to machine learning algorithms and techniques
Supervised learning (classification and regression)
Unsupervised learning (clustering and dimensionality reduction)
Evaluation and validation of machine learning models
Introduction to big data and its challenges
Hadoop ecosystem and distributed computing frameworks
Data processing with Apache Spark
Analyzing large-scale datasets using MapReduce
Techniques for analyzing text data (tokenization, stemming, etc.)
Sentiment analysis and opinion mining
Natural Language Processing (NLP) fundamentals
Text classification and topic modeling
Understanding time series data and its characteristics
Techniques for time series decomposition and forecasting
Seasonal and trend analysis
Introduction to ARIMA and other time series models
Ethical considerations in data analytics
Privacy protection and data anonymization techniques
Legal and regulatory frameworks (GDPR, CCPA, etc.)
Ensuring fairness and avoiding bias in data analytics
The course content is subject to customization and may vary based on the specific training provider or organization offering the course.
No limits on learning, no limits on duration, no limits on salary, no limits on interviews, learn as much as you can & get ready for your first job.
Flexible training duration
Weekday | Weekend | On avalability
Practical based approach
Individual 1 to 1 dedicated training
Professional developers as your trainer
Skill oriented customised training on your need
Free post training support
6 months training duration
Monday to Friday (Regular office)
Live & Direct work with team
Individual 1 to 1 training
+Unlimited placement, Dual job opportunity.
Get your first job offer on the day of joining.
IN as fresher OUT as experienced developer
We strive to provide quality of learning step by step, that exactly what you want!
