Proficiency in Python programming language is an essential prerequisite for anyone pursuing a career in data science. TokSkill's Data Science with Python course is a comprehensive program that equips individuals with a thorough understanding of Python's data analytics tools and techniques. The course follows a hands-on learning approach, enabling participants to gain practical experience in using Python for data science, including data wrangling, mathematical computing, and other essential concepts. Take the leap today and enroll in TokSkill's Data Science with Python program to unlock your full potential and thrive in the fast-paced and ever-evolving world of data science.
Additional Benefits of our Program
- Data Science Industry Experts Community
Gain exclusive access to our Alumni community and connect with industry experts in data science through Discord, Telegram, and WhatsApp. This network is available 24/7 for doubt clearing and support.
We guarantee a 3-month internship program with a 100% placement rate. This program provides invaluable real-world experience and networking opportunities to kickstart your career in data science.
Data Science Career Outlook
- Multiple Career Paths including Data Scientist, Data Engineer, Data & Analytics Manager etc.
- 11 Million+ Job Opportunities Globally
- Avg. Salary: $1,14,000 USD Globally
- 28% Annual Career Growth
- High Demand in Diverse Industries including Tech, Finance, E-Commerce, Healthcare etc.
Program Team
- Khalid Nabeel: Accomplished Data Scientist with years of experience @Google.
- Jaitra Bopanna: Highly skilled Python Expert with a proven track record at Study.net.
- Debasis: Seasoned Business Analyst with prior experience at Tesla and JP Morgan.
- Shabaz Ali: Talented Data Analyst with a successful stint at Harman.
- Balaji L: Accomplished Data Engineer with a wealth of experience at Alcon and Deloitte.
- Mohd. Arbaz: Proficient Machine Learning Expert with a history of developing intelligent solutions at Study.net.
Live Classes Timing
10:00 AM - 12:00 PM.
02:00 PM - 04:00 PM.