Are you considering taking a course to boost your data science and data engineering skills? Look no further! I recently discovered a fantastic program called Introduction to Python for Data Science.
As a data enthusiast myself, I’m excited to share my in-depth review of this course on Data Driven Daily.
Quick Overview: Introduction to Python for Data Science
This comprehensive, short-duration curriculum is perfect for data scientists, data engineers, analysts, and researchers who want to level up their Python expertise. But don’t worry if you’re a beginner or a little rusty with Python syntax—the course is designed for both practitioners and beginners.
Starting From the Ground Up
Before the learning experience begins at Introduction to Python for Data Science, the course offers carefully designed self-paced learning modules that help students get up to speed with Python fundamentals. This pre-training ensures everyone is well-prepared for the live sessions, creating a smooth transition into more advanced topics.
Instructor-Led Training, Office Hours, Mentoring, and More
Introduction to Python for Data Science boasts a wealth of resources to make the learning experience engaging and enjoyable:
- Instructor-led, live training sessions
- Daily, live office hours for homework support
- Hundreds of code samples for practice
- Cloud-based compute tools, inline code editor, and code repositories
- Hundreds of Pandas, NumPy, Seaborn, matplotlib, and scikit-learn code samples
- Mentoring for class projects
- One-year access to all supplementary learning material
- A verified certificate from The University of New Mexico Continuing Education
Curriculum: What Can You Expect To Learn?
The curriculum covers all the essential aspects of Python for data science and data engineering:
- Python Fundamentals
- NumPy and Pandas
- Data Wrangling
- Data Exploration and Visualization
- REST APIs and Data Pipelines
- Machine Learning with scikit-learn
- Mentored Project
Upon completion, students earn a data science certificate in association with the University of New Mexico Continuing Education, verifying their skills and helping them stand out in the job market.
This is a great addition to your resume if your looking to bolster your chances of getting that next career bump.
Pricing: How Much Will It Set Me Back?
Data Science Dojo has a few different pricing options – and often if you get in early you can get a massive 40% discount!
Their entry level is Dojo and comes in at $599 ($999 full-price), next is Guru coming in at $779 ($1,299) and finally Sensei will set you back $1,499.
Note: you will need to opt for atleast the Guru tier if you want an official certificate from the University of New Mexico,
Check out their pricing and see if they have a sale on right now.
What I Liked
- In-depth Curriculum: The course covers a wide range of topics, ensuring students gain a thorough understanding of Python for data science and data engineering.
- Flexible Learning: The self-paced pre-training modules allow students to learn at their own pace before attending the live sessions.
- Expert Instructors: The instructors are knowledgeable and experienced, providing invaluable guidance throughout the course.
- Practical Experience: The course offers hands-on learning through various code samples, assignments, and a mentored project, enabling students to apply their skills in real-world scenarios.
- Networking Opportunities: The in-person training sessions provide a great opportunity to connect with fellow data enthusiasts and build lasting professional relationships.
What Might Be A Bummer
- Short Duration: The course is designed to be comprehensive yet short in duration, which may be challenging for some students to absorb all the information in a limited time.
- Cost: The program may be considered expensive for some individuals, although the benefits of learning and the potential for career advancement can outweigh the initial investment.
Testimonials
But don’t just take my word for it—students who have taken Introduction to Python for Data Science rave about their experiences. They praise the in-depth curriculum, supportive instructors, and practical learning approach that gave them the confidence to tackle real-world data challenges.
What is Data Science Dojo?
Data Science Dojo is a leading educational institution that empowers individuals and organizations to excel in the rapidly growing field of data science. With a focus on providing practical, hands-on training, Data Science Dojo offers a range of courses and bootcamps designed to cater to various skill levels and professional backgrounds.
The company’s team of experienced and dedicated instructors are committed to helping students build a strong foundation in data science and engineering concepts, equipping them with the tools and techniques necessary to succeed in the competitive job market.
By fostering a supportive learning environment and emphasizing real-world applications, Data Science Dojo has earned a reputation for delivering high-quality education that transforms lives and drives innovation.
Closing Thoughts: Give it a go
If you’re looking to improve your data science and data engineering skills, I highly recommend considering the Introduction to Python for Data Science course. It’s a fantastic investment in your future, and you’ll walk away with a trusted and proven skill set that’s in high demand.
In summary, the Introduction to Python for Data Science course is an excellent choice for those looking to advance their skills in Python, data science, and data engineering.
The comprehensive curriculum, expert instructors, and hands-on learning approach make it an invaluable experience for students at all levels. The networking opportunities and verified certificate add to the benefits of this course, making it a solid investment in your professional development.
We also took to the time to review plenty of other data science bootcamps in our popular blog post.
Ben is a full-time data leadership professional and a part-time blogger.
When he’s not writing articles for Data Driven Daily, Ben is a Head of Data Strategy at a large financial institution.
He has over 12 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.