Starting a Career in Data Science: Project Portfolio, Resume and Interview Process Training Course
Gain the skills you need to advance your career. This course offers hands-on learning, expert guidance, and real-world applications designed to help you grow.
Course Overview
| Course Title | Starting a Career in Data Science: Project Portfolio, Resume and Interview Process Training Course |
| Organization | Tech For Development (T4D) |
| Venue | Tech For Development (T4D) Training Center along Tala Road, Runda, Nairobi |
| Duration | 5 days |
| Target Industries |
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| Target Job Roles |
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| Course Fees (Face-to-Face) | USD 1,100/KES 75,000 (Exclusive of VAT) |
| Course Fees (Virtual) | USD 1,000/KES 70,000 (Exclusive of VAT) |
| Training Modes | Virtual and face-to-face training |
| Payment | Payment should be made to the Tech For Development (T4D) bank account on or before the start of the course |
| Accreditation | Tech For Development Certificate of Course Completion |
Course Overview
Data science is a growing requirement for most institutions and companies to aid, improve or sustain their progression and projects. Therefore, employers are critical to hire the best professions in data science positions. This course aims to sharpen any profession and prepare them for their careers in data science, making them the best and competitive in the job market. This course focuses on giving those who take it a better understanding of the job markets, what is required of them in data science careers and what employers will look for to give them a front foot in the market. it will also provide an insight on techniques on how to get a job in data science, prepare for an interview and how to pass in any interview.
Duration
5 days
Target Audience
- Aspiring Data Scientists
- Career Changers
- Data Analysts
- Industry Professionals
- Job Seekers
- Self-learners
Organizational Impacts
- Enhanced recruitment of qualified data science candidates.
- Improved employee skill sets in data-driven decision-making.
- Increased overall productivity through effective data utilization.
- Strengthened company reputation as a hub for data talent.
- Better alignment of data science initiatives with business goals.
Personal Impacts
- Improved employability and job prospects in the data science field.
- Enhanced understanding of the data science career landscape.
- Development of a robust project portfolio to showcase skills.
- Increased confidence in job interviews and professional networking.
- Empowerment to pursue a successful career in data science.
Course Objectives
- Understand various data science roles and their responsibilities.
- Build and showcase impactful data science projects.
- Develop a strong data science resume.
- Create a compelling cover letter.
- Prepare for different types of interviews.
- Master networking techniques and leveraging informational interviews.
Course Modules
Course Outline
Module 1: Course Overview and Interview Preparation
- The Data Science Knowledge You Need
- Types of Data Science Roles
- The Interview Process Structure
- What Interviewers Look For
- How to Get the Most from Your Interview Preparation
- Case Study: A successful candidate shares their experience of transforming their interview preparation, resulting in landing a job at a leading tech company.
Module 2: Portfolio Development
- What Is a Data Science Project
- The Projects You Should Do
- How to Differentiate Your Projects
- Where to Showcase Your Projects
- GitHub Profile Best Practices
- Kaggle Profile Tips
- Case Study: An analysis of a data scientist's portfolio that impressed employers through innovative projects and effective presentation on platforms like GitHub and Kaggle.
Module 3: Resume and Cover Letter Essentials
- How to Structure Your Resume
- Writing About Work and Projects
- Customizing Your Resume
- Creating a Virtual Resume
- Resume Checklist
- Crafting the Perfect Cover Letter
- Case Study: Reviewing a candidate's before-and-after resume and cover letter that led to multiple interview invitations, showcasing the impact of tailored applications.
Module 4: Networking and Interview Strategies
- How Candidates are Selected
- Networking for Data Scientists
- Leveraging Your Resources
- Conducting Informational Interviews
- Reaching Out to Recruiters
- Case Study: A data scientist's journey of leveraging networking strategies, resulting in securing a referral and a job offer from a prestigious organization.
Module 5: Interview Formats and Success Strategies
- The Phone Interview Overview
- What to Expect
- How to Prepare for Phone Interviews
- Strategies for Succeeding in Phone Interviews
- Case Study: A candidate recounts their successful phone interview experience, highlighting effective preparation techniques that helped them stand out to employers.
Course Administration
Methodology
Instructor-led sessions use a blended learning approach combining presentations, guided practical exercises, web-based tutorials, and group work, delivered by seasoned industry experts. All facilitation and course materials are in English, so participants should be reasonably proficient in the language.
Accreditation
Upon successful completion of this training, participants will be issued a Tech For Development Certificate of Course Completion certified by the National Industrial Training Authority (NITA).
Training Venue
The training will be held at the Tech For Development Training Centre. The course fee covers the course tuition, training materials, two break refreshments, and lunch. All participants will additionally cater to their travel expenses, visa application, insurance, and other personal expenses.
Accommodation & Airport Transfer
Arranged upon request.For reservations contact the Training Officer:
Email: [email protected]
Phone: (+254) 790 824 179
Tailor-Made
This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our T4D Training Centre or at a convenient location.
Payment
Payment should be transferred to the T4D account through a bank on or before the start of the course. Send proof of payment to [email protected].
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