Course Design By
Nasscom & Wipro
Comprehensive Understanding of Data Science: Provide a solid foundation in data science principles, including machine learning, statistical analysis, and data visualization.
Practical Programming Skills: Develop proficiency in programming languages commonly used in data science, such as Python and R.
Real-World Problem Solving: Enable participants to apply theoretical concepts to solve real-world problems using data-driven approaches.
Hands-On Experience: Offer extensive hands-on training through projects and case studies to build practical experience.
Industry-Relevant Curriculum: Ensure the curriculum is aligned with current industry standards and practices to make participants job-ready.
Analytical Thinking and Decision Making: Foster analytical thinking and data-driven decision-making skills.
Preparation for Advanced Certifications: Prepare participants to pursue advanced data science certifications and further their professional qualifications.
Career Advancement: Enhance career prospects by providing the skills needed to secure roles such as data analyst, data engineer, and data scientist.
Data Analyst: Starting salaries range from INR 3 to 5 lakhs per annum, with experienced analysts earning between INR 6 to 8 lakhs per annum.
Data Scientist: Entry-level data scientists can expect to earn INR 6 to 8 lakhs per annum, while those with more experience can command salaries of INR 10 to 15 lakhs per annum.
Data Engineer: Initial compensation typically falls between INR 4 to 6 lakhs per annum, with experienced professionals earning INR 8 to 12 lakhs per annum.
Machine Learning Engineer: Starting salaries are in the range of INR 5 to 7 lakhs per annum, with seasoned engineers earning between INR 10 to 18 lakhs per annum.
Business Intelligence Analyst: Entry-level analysts can expect to earn INR 3 to 5 lakhs per annum, with experienced professionals earning between INR 6 to 10 lakhs per annum.
Job Opportunities: Eligible for roles like data analyst, data scientist, and machine learning engineer.
High Salaries: Competitive pay for both entry-level and experienced positions.
Skill Development: Gain expertise in data analysis, machine learning, and data visualization.
Industry Flexibility: Opportunities across IT, finance, healthcare, retail, and more.
Certification Readiness: Prepared for advanced data science certifications.
Leadership Potential: Pathway to senior roles like data science manager or chief data officer.
Data Collection and Cleaning: Gather and preprocess large datasets.
Data Analysis: Identify trends and patterns using statistical methods.
Model Development: Create predictive models and machine learning algorithms.
Data Visualization: Develop dashboards and reports to present findings.
Collaboration: Work with stakeholders to understand and meet data needs.
Model Optimization: Monitor and refine models for better performance.
Documentation: Maintain detailed records of methodologies and results.
Industry Trends: Stay updated with the latest data science techniques.
Data Security: Ensure data privacy and compliance.
Mentoring: Guide and train junior data scientists.
Information Technology (IT) - Growing demand for data-driven solutions.
E-commerce - Optimizing supply chains and personalizing customer experiences.
Healthcare - Enhancing diagnostic accuracy and healthcare delivery.
Finance and Banking - Detecting fraud and developing predictive financial models.
Education - Personalizing learning experiences and improving educational outcomes.
Telecommunications - Analysing customer data and optimizing network performance.
Manufacturing - Predictive maintenance and supply chain optimization.
Retail - Understanding consumer behavior and managing inventory.
Travel and Tourism - Enhancing customer experiences and optimizing pricing.
Real Estate - Analysing market trends and predicting property values.
Machine Learning
Statistical Analysis
Data Visualization
Programming in Python/R
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Course Design By
Nasscom & Wipro
Course Offered By
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The duration varies, typically ranging from 3 to 6 months depending on the program.
The course covers topics like machine learning, statistical analysis, data visualization, and programming in Python/R.
The best institute is often considered based on faculty expertise, course content, and alumni success.
Basic knowledge of programming and statistics is recommended but not mandatory for beginners.
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