Python
NumPy
Pandas
Matplotlib
SQL
PowerBI
Supervised Learning
Unsupervised Learning
Data Scientist
Data Engineer
Data Analyst
Business Analyst
Course Duration: | 6 months of training classes with a hands-on project to practice. Provision of an optional 12 months internship including the training period. |
Curriculum Delivery: | Online training, Onsite training, Virtual training, Corporate training. |
Timings & Schedules: | Both on Weekdays / Weekends |
Extras: | Mock Tests, Interview Questions & Answers will be covered along with the course. |
LAB Facility: | Our training courses are designed to provide an optimal learning environment. For students to learn to code or access our Cloud Platform, we have a well-equipped lab facility with simulation tools and powerful processors that can run complex simulations and display scenes. Qualified lab tutors can provide students with the most up to date technologies and are experts in their fields. In order to give our interns the finest training environment for learning different coding and software development skills, we also offer internships in this facility. |
Course Contents: | Python, NumPy, Pandas, Matplotlib, SQL, PowerBI, Supervised Learning, Unsupervised Learning |
Career Gap Courses in Computer Science and Information Technology with a duration of 6 months, are specifically designed to help individuals re-enter the workforce after a break. To keep participants aware of industry standards and practices, these courses offer a thorough study and update of the most recent technology breakthroughs. Data analysis, cybersecurity, software development, and programming languages are important areas of concentration. These courses attempt to close the gap between prior expertise and the changing expectations of the IT sector by providing practical skills and key subjects, allowing students to return to their employment with more confidence.
The Data Science Training is designed to equip students with the skills and knowledge needed to analyze and interpret complex data to drive decision-making and innovation. Covering a broad range of topics, the course begins with an introduction to data science principles and the data science lifecycle, including data collection, cleaning, and preparation. Students will delve into exploratory data analysis (EDA) and learn how to visualize data effectively using various tools and techniques.
Throughout the course, emphasis is placed on practical applications and project-based learning, ensuring that students gain experience in building and deploying data science solutions. By the end of the course, students will be adept at using industry-standard tools and technologies, understanding data ethics and privacy concerns, and preparing for careers in the dynamic field of data science.
→ Job Seekers, Freshers, Web Developers, Web Designers, Software Developer, Graduates, IT Professionals.
→ Optional post-completion Internship program
→ Live project during internship
→ Individual Attention
→ Course completion certificate
→ Experience Certificate
→ Career Guidance
→ Placement Assistance
→ Interview Assistance with Mock Interviews