Data Science
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Data Science Course Curriculum
Get started with the Advanced Executive Program in Data Science Explore everything about this unique program covering advanced concepts of cybersecurity and kickstart your journey as a cybersecurity professional
The Enterprise Infrastructure Security course will enable learners to gain knowledge and skills in a series of advanced and current concepts in cyber security, and related to enterprise and infrastructure security. After the completion of this module, learners will have a comprehensive understanding of the NICE framework, security controls, networking concepts, traffic analysis, packet analyzers, sniffers, firewalls, SIEM, VLAN, VPN, identity and access management, and much more
The Application and Web Application Security course will enable learners to gain knowledge and skills in OWASP tools and methodologies, insecure deserialization, clickjacking, black box, white box, fuzzing, symmetric/asymmetric cryptography, hashing, digital signatures, API security, patch management, and much more.
Malware, specifically ransomware, costs businesses more than $75 billion per year. These attacks continue to be a threat to the security of companies. In this module, you will get an overview of how to detect, analyze, and protect yourself and your company from ransomware attacks
This module provides you with the hands-on training required to master the techniques hackers use to penetrate network systems, helping you fortify your system against it. You will also gain an understanding of the finer nuances of advanced hacking concepts, penetration testing, and vulnerability assessment.
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About Data Science
- Introduction to Data Science
- Overview of data science and its importance
- Understanding the data science lifecycle
- Roles and responsibilities of a data scientist
Data Manipulation and Cleaning
- Data wrangling techniques
- Handling missing values
- Data transformation and normalization
- Feature engineering
Statistics and Probability
- Descriptive statistics (mean, median, mode, variance, etc.)
- Probability distributions
- Inferential statistics (hypothesis testing, confidence intervals)
- Correlation and causation
Data Visualization
- Principles of effective data visualization
- Tools and libraries for visualization (e.g., Matplotlib, Seaborn, Tableau)
- Creating various types of charts and plots
- Communicating insights through visualizations
Programming for Data Science
- Introduction to programming languages commonly used in data science (Python, R)
- Writing efficient and clean code
- Libraries and packages for data analysis (e.g., Pandas, NumPy, SciPy)
Machine Learning
- Supervised learning (regression, classification)
- Unsupervised learning (clustering, dimensionality reduction)
- Model evaluation and selection
- Overfitting and underfitting
Advanced Machine Learning Techniques
- Ensemble methods (bagging, boosting, stacking)
- Deep learning basics (neural networks, backpropagation)
- Natural language processing (NLP)
- Time series analysis and forecasting
Big Data Technologies
- Introduction to big data concepts
- Tools for big data processing (Hadoop, Spark)
- Working with large datasets
- Cloud computing for data science
Data Ethics and Privacy
- Ethical considerations in data science
- Data privacy laws and regulations (e.g., GDPR, CCPA)
- Responsible data use and sharing
- Bias and fairness in algorithms
Capstone Project
- Applying knowledge to a real-world problem
- End-to-end data science project execution
- Data collection, cleaning, analysis, and model building
- Presenting findings and insights
Career Opportunities After Data Science Training
Information Security Analyst
Ethical Hacker/Penetration Tester
Data Analysts
Data Scientist:
Machine Learning Engineer
Information Security Analyst
An information security analyst safeguards an organization’s digital assets and sensitive information from cyber threats and data breaches. They assess IT infrastructure and develop strategies like firewalls, encryption, and authentication to ensure confidentiality and prevent potential threats.
Average Salaries
₹ 3L – ₹ 12LPer AnnumHiring Companies
Ethical Hacker/Penetration Tester
Ethical hackers, also known as penetration testers, are hired by organizations to identify vulnerabilities in their systems and networks by simulating cyberattacks. They help organizations strengthen their security by finding and fixing weaknesses before malicious hackers can exploit them.
Average Salaries
₹ 2L – ₹ 18.4LPer AnnumHiring Companies
Data Analysts
- Role: Data analysts interpret data to provide actionable insights, support decision-making processes, and create reports and dashboards. They focus on processing and performing statistical analyses on existing data sets.
- Skills Required: Strong skills in SQL for database querying, proficiency in Excel, and familiarity with data visualization tools (e.g., Tableau, Power BI). Basic programming skills in Python or R can also be beneficial.
- Industries: Marketing, sales, finance, government, and healthcare
Data Scientist:
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- Role: Data scientists analyze large sets of structured and unstructured data to uncover insights, create predictive models, and help organizations make data-driven decisions. They use statistical methods, machine learning algorithms, and data visualization techniques.
- Skills Required: Proficiency in programming languages like Python or R, knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), strong statistical and analytical skills, and experience with data visualization tools (e.g., Tableau, Power BI).
- Industries: Technology, finance, healthcare, e-commerce, and many others
ab Content
Machine Learning Engineer
- Role: Machine learning engineers design, build, and deploy machine learning models. They work closely with data scientists to implement algorithms that can be integrated into software applications, products, or services.
- Skills Required: Expertise in programming languages like Python, Java, or C++, knowledge of machine learning frameworks (e.g., TensorFlow, Keras, Scikit-learn), and a strong understanding of computer science fundamentals and software engineering principles.
- Industries: Technology, automotive, finance, healthcare, and any sector where automation and intelligent systems are valuable
I was good experience and they provide real time projects and trainers are teaching very nicely and also teaching new skills and technologies.
It was really a very nice experience. Good teachers and loved the ambience too. They gave me proper guidance for my future and also helped me to gain more knowledge. Overall loved it.
100% Job orientated in Course. Graduates & Working Professional. Become a Certified Java Full stack development . Globally Accepted &100% Placement.
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